The Design and Effectiveness of Online Collaborative Work

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This post is provided by guest blogger, Tania Pacheco, graduate student University of St. Francis, MS Talent Development program.

Online learning has become a commonplace method of instruction due, in part, with the onset of the pandemic. This article examines how online collaborative learning is designed for the higher education environment and how specific design choices influence its effectiveness. Using a survey of online learners, the study invited students to share their experiences with the design of online group work in relation to group size, formation methods, collaboration type, and duration, along with their relationship to teaching and social presence. Results showed that collaborative work predominately occurs within small, randomly assigned groups focused on discussions, assignments, or peer reviews for varying lengths of time. While many students perceived online collaborative work as beneficial for learning and engagement, others reported neutral or mixed experiences due to coordination and participation challenges. Higher levels of social and teaching presence were associated with allowing students to self-select their groups and incorporating peer review activities. Overall, the study emphasizes that online learners value being able to provide input into the process of collaborative work in their online courses and that this purposeful, learner-centered design is critical for effective online collaborative work.

This article is an excellent resource for trainers, higher education instructors, and instructional designers that are responsible for creating online learning environments and wish to foster a positive e-learning experience. Effective instructional methods in online education differ from methods that are effective in other learning environments due to the lack of personal connection and face-to-face interaction. The study’s findings suggest that an instructor’s level of understanding of their student’s needs and how the instructional strategy being used relates to various learners’ requirements, enabling them to develop more effective learning experiences. Using the results of the study as a structural framework for integrating collaborative activities in an online environment would serve as a beneficial tool to inspire active participant engagement and to generate consistent feedback for future improvements to the learning experience.

Reference:

Oyarzun, B., Kim, S., Maxwell, D. et al. (2025). The design and effectiveness of online collaborative work. Journal of Computing in Higher Education. https://doi.org/10.1007/s12528-025-09472-2

COI Framework Shift to Self-Organized Discovery

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This post is provided by guest blogger, Rachel Dobrich Ruffetti, a graduate student at the University of St. Francis in Joliet, working towards the Talent Development Certificate.

The article, “A Distributed Perspective to the Community-of-Inquiry Framework for Distance Education” by Piera Biccard (2025), revises the original Community-of-Inquiry (COI) framework by strengthening its underlying structure. The original framework includes teaching, social, and cognitive presence, which support well-organized online discussions, meaningful connections among online learners, and critical thinking in digital environments. Biccard emphasizes the importance of incorporating learners more directly into this model. The author advocates for a distributed approach to learning, where responsibility is shared across people, content, and tools through intentional technology integration. Students should transition from passive recipients to active contributors, bringing their unique skills and knowledge to the developing learning community. Technological tools play a critical role in this shift, fostering self-organized discovery and deeper engagement in online settings.  

This peer-reviewed study offers valuable insight for course designers and instructors aiming to enhance online learning environments. Biccard (2025) effectively integrates literature and research to expand the original COI model, illustrating how digital tools can promote learner autonomy, collaboration, and engagement. By emphasizing distributed teaching and learner agency, the article shifts technology from a supplemental to a core feature of intentional design. Instructors can leverage the interaction among participants, content, and tools to cultivate meaningful teaching, social, and cognitive presences. This resource will help educators create robust, student-centered learning experiences that encourage students to interact, share knowledge, and listen to other perspectives.

Reference  

Biccard, P. (2025). A distributed perspective to the community-of-inquiry framework for distance education. Open Learning, 40(2), 136–151. https://research-ebsco-com.ezproxy.stfrancis.edu/linkprocessor/plink?id=938137ea-9c73-35c0-a977-a1c602b4d145  

Power of AI for Teachers

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This post is provided to you by guest blogger, Adam Gurke, graduate student at University of St. Francis, Learning and Development Manager certificate student.

The article discusses how AI needs to be used in classrooms for teachers and students to prepare students for careers in the future. AI in classrooms is increasing for students, but also teachers. Currently, there are many AI tools geared towards teachers to support students and their learning. “If we want our students to be ready for their future careers, we must start teaching them about AI” (Poth, 2025). This source provides different AI tools for schools to use with their students such as SchoolAI, MagicSchool AI, and Eduaide to name a few. 

This source can be utilized by educators and school districts to learn about the various options for AI in education. AI helps teachers with elearning and lesson planning for teachers. This source provides examples for using AI in the classroom and the benefits for AI for students and teachers. This source also provides information for meeting the needs of all learners including language language learners.

References

Poth, R. D. (2025, June 10). AI resources for teachers. Edutopia. https://www.edutopia.org/article/ai-resources-teachers?utm_source

Building Better eLearning: Management and Support Strategies That Work

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This post is provided by guest blogger, Stephanie Lawrence, graduate student at the University of St. Francis, MS in Talent Development program.

In the article, Supporting e-learning in the workplace: A framework for practice, Chyung and Kickul (2023) lay out a comprehensive plan for managing eLearning in the workplace. They explain how successful programs go beyond just delivering content, they require thoughtful planning, leadership support, and tools that keep learners engaged and supported. Their framework stresses learner-centered design, hands-on help when needed, and ongoing evaluation to make sure training stays relevant and effective over time. Continuous improvement is critical for aligning training with business goals.

This article does a great job making connections between strategy and what actually helps people learn. Chyung and Kickul (2023) combine research with real-world examples, enabling application. One thing that could improve the article is a bit more focus on change management, especially when teams are new to eLearning. The shift from traditional learning to eLearning can be difficult for some audiences. Still, this article is valuable for talent development professionals and training teams who are working on larger digital learning efforts.

Categories: Instructional Design, Adult Education, E-learning

Reference:

Chyung, S. Y., & Kickul, J. (2023). Supporting e-learning in the workplace: A framework for practice. Performance Improvement Quarterly, 36(2), 137–153. https://doi.org/10.1002/piq.21486

E-Learning Success is in Student Engagement

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This post is provided by guest blogger, Kurt Krauss, graduate student at the University of St. Francis in Joliet, MS in Talent Development program.

Recently, I came across an article from Northern Illinois University on “Recommendations to Increase Student Engagement in Online Courses” that offered a number of fact-backed suggestions for student success in E-learning. The article offered five categories including: Setting Expectations and Model Engagement, Building Engagement and Motivation with Course Content and Activities, Initiating Interaction and Create Faculty Presence, Fostering Interaction between Students and Create a Learning Community, and Creating an Inclusive Environment. In 30 talking-point specific subcategories, they reiterated that how the professor regularly engages with the student and creation of a virtual classroom will ultimately be determining factors in the student’s learning experience.

In researching credible sources in higher education, I often look to articles published by other accredited universities and colleges; obviously Northern Illinois University is one of them. Backing their findings, they cited studies from several educational journals and additional publications. Online learning is an evolving field, however the constant will remain student engagement in learning.

Reference: Northern Illinois University Center for Innovative Teaching and learning. (n.d.). Recommendations to increase student engagement in online courses. https://www.niu.edu/citl/resources/guides/increase-student-engagement-in-online-courses.shtml

Evaluating the Future of e-Learning Platforms

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This post is provided by guest blogger, Leah Koncir, graduate student University of St. Francis, MS

In “LMS in 2025: top trends transforming the future of education,” S. Smith (2024) explores emerging trends in Learning Management Systems (LMS) that are set to redefine educational delivery. The article highlights advancements such as AI-driven personalization, data analytics, mobile-first learning, gamification, collaborative learning, blockchain for credentialing, and immersive technologies like AR and VR.

While the article offers a comprehensive overview of these innovations, it could benefit from a more critical analysis of potential challenges in implementing such technologies. For instance, the integration of AI and data analytics raises concerns about data privacy and the need for robust security measures. Additionally, the adoption of immersive technologies may face obstacles related to cost and accessibility. Addressing these considerations would provide more balanced perspective on the future of LMS in education.

Category: E-Learning

Reference:

Smith, S. (2024, January). LMS in 2025: Top trends transforming the future of education. eLearning Industry. https://elearningindustry.com/lms-top-trends-transforming-the-future-of-education

Perils and Promise of the Shiny New Object

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This post is provided by guest blogger, Suzanne Gillespie, graduate student at the University of St. Francis in Joliet, MS in Talent Development program.

Dannewitz’s (2025) TD Magazine article, “All That Glitters Is Not Gold” argues that while emerging learning technologies can feel exciting and futuristic, L&D professionals must resist being dazzled by novelty alone. The article emphasizes distinguishing hype from tools that genuinely improve performance. It encourages practitioners to evaluate technologies based on clear business needs, measurable outcomes, and practical integration into existing workflows. Rather than chasing flashy demos—like AI chatbots or immersive VR—the piece urges focusing on solutions that solve real problems, scale sustainably, and enhance everyday learning experiences. Ultimately, meaningful impact—not trendiness—should guide technology adoption.

TD Magazine, a publication from the Association for Talent Development, is a reputable source within the learning and development field, so the article carries solid credibility, especially for practitioners seeking grounded perspectives on emerging technologies. The article “All That Glitters Is Not Gold” is useful because it challenges readers to look past hype and evaluate tools based on real organizational impact. Its emphasis on strategic decision‑making makes it valuable for L&D leaders, instructional designers, and HR professionals who must justify technology investments. While the article offers practical guidance, it could go further by providing downloadable evaluation frameworks or concrete case studies. Still, it serves as a thoughtful reminder to prioritize substance over novelty.

Reference

Dannewitz, B. (2025, October 31). All that glitters is not gold. TD Magazine. https://www.td.org/content/td-magazine/all-that-glitters-is-not-gold  

The Opportunities of GenAI in Higher Education

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This post is provided by guest blogger, Jocelyn Lupercio, graduate student at the University of St. Francis in Joliet, MBA program.

This article on the NIH website highlights the current transformation GenAI is having on higher education. The use of GenAI in higher education has become so conventional that now more than half of students report using GenAI and much of that use being undetected by educators. While GenAI has created new concerns in higher education, GenAi also offers a range of opportunities for personalized learning and the expansion of access to knowledge. The article frames GenAI as a need for gradual transformation to ensure that human centered values remain at the forefront of higher education

While the article offers opportunities for GenAI in higher education and highlights the significance of institutional responsibility, the suggestions offer limited details, evidence and data and remain very conceptual. The discussion could be strengthened by evidence derived from case studies and offering the student perspective as well.

Reference

Sejdiu, N. P., & Sejdiu, S. (2025). The quiet transformation of higher education in the AI era. Open Research Europe, 5, 249.

Empowering eLearning: Student Choice Matters

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This post is provided by guest blogger, Hailey Kaddatz, graduate student at the University of St. Francis in Joliet, MS in Talent Development program.

Managing and supporting elearning depends on the different ways people learn (Eidenberger & Nowotny, 2022). Today’s students are used to having control over what they learn. If you provide students choices in school, learning effectiveness will increase. More importantly, this approach encourages students to take control of their own education. In the end, it brings everyone benefits.

With data drawn from up-to-date educational research and the best practices in eLearning, the source is trustworthy. It may not be very productive for teachers. They may struggle to improve student engagement. It might be challenging for them to make their own learning idea match the students. Administrators and teachers with eLearning programs and instructional designers can all find this information useful.

Reference:
Eidenberger, M. and Nowotny, S. (2022) Video-based learning compared to face-to-face learning in psychomotor skills physiotherapy education. Creative Education, 13, 149-166. doi: 10.4236/ce.2022.131011.

Are video shorts the new method?

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This post is provided by guest blogger, Anthony Panzella, graduate student at the University of St. Francis in Joliet, MS in Talent Development program.

The article from EDUCAUSE Review explains how generative artificial intelligence (GenAI) can be used to convert lengthy instructional videos into a series of engaging, short video lectures that enhance student engagement and learning. It describes a case where an instructional design professor used GenAI to restructure a long lecture into micro-lectures with interactive elements such as quizzes, visual aids, and voiceovers, making the content more accessible and appealing. The article discusses how clear prompting, content segmentation, and review of AI-generated outputs contribute to creating short videos that align with learning goals and support personalized learning experiences.

The source is reliable because it is published by EDUCAUSE Review, a respected outlet focused on higher education technology trends and instructional innovation. The detailed account of how GenAI was applied offers a practical example that educators and instructional designers can adapt for their own courses or training programs. This resource is especially useful for professionals seeking ways to improve learner engagement in online or blended environments and to reduce the time required for video content creation. However, readers should consider the need for instructor review and revision to maintain accuracy and pedagogical quality. The article would interest faculty, instructional designers, and training specialists exploring AI-enhanced learning tools.

Zheng, H. (2025, June 17). Leveraging GenAI to transform a traditional instructional video into engaging short video lectures. EDUCAUSE Review. Retrieved from https://er.educause.edu/articles/2025/6/leveraging-genai-to-transform-a-traditional-instructional-video-into-engaging-short-video-lecturesLinks to an external site.