This post is provided by guest blogger, Darryl Barrios, graduate student University of St. Francis, MS Training and Development program
Despite the growth of eLearning, for most, education continues to mean classroom sessions with teachers. As the world continues to evolve, so does education. While most organizations are onboard with eLearning, it takes time to learn to skills and techniques to make it successful. Implementing eLearning requires three basic steps: Planning, implementation itself, and evaluation. During implementation, it is important to keep common challenges, such as lack of student engagement and technological hurdles, at the forefront. Assessing your needs, planning your courses and goals, and communicating with all parties throughout the process are all key to a successful launch.
Sergi Movchan’s (2025) article How to Implement eLearning In an Effective Manner? provides a straightforward explanation of the process of identifying the process for implementing an eLearning system. He begins by identifying the common challenges that organizations face during this process. This is followed by outlining basic tips that any organization can follow to ensure a successful launch. Throughout the article, he links to other articles that help expand on many of the steps that are required. This article is a great primer for anyone who is looking to begin the process of implementing an eLearning program.
This post is provided by guest blogger, Gerald Edwards Jr., graduate student University of St. Francis, MS Training and Development program
There is a massive amount of digital data available on any number of subjects. AI has pushed the boundaries of big data. Gleaning useful information from endless search parameters is an infinite challenge, especially in the e-learning setting. The use of AI and big data mining makes it nearly impossible for students, in the time frame of semester course work, to make meaningful connections between various subject matters. There is an emerging tool that is indispensable to students and researchers at all levels of education, but specifically in the e-learning setting.
An article published in the journal Heliyon, analyzes the available peer reviewed published research literature on the use of data graphs as an effective search technology which is highly adaptable and suited for the digital learning environment. The authors provide a systematic appraisal of user usefulness and successful research outcomes in the digital learning environment when searching topics using institutionally compiled data graphs. Data graphs allow seemingly independent information variables to interconnect and return more meaningful data to the user through AI and human compiled related data. This information is useful when students and institutions are interested in a comprehensive understanding of a specific topic. Data graphs have been developed in other areas but are emerging as a invaluable tool for higher education students and instructors participating in the e-learning environment.
Abu-Salih, B. & Alotaibi, S. (2024). A systematic literature review of knowledge graph construction and application in education. Heliyon, (10)3. https://doi.org/10.1016/jheliyon.2024.e25383
This post is provided by guest blogger, Michelle Edwards, graduate student University of St. Francis, MS Training and Development program.
This article focused on changes that were implemented for students of management education and management education educators in the post COVID-19 era. The world had to pivot in 2020, and adult learning was no exception. This article explained changes that transformed learning. Management education is unique in such that the education is provided for business leaders, administrators and provides professional or expert advice. This is a specialty area of education.
This was an awesome article; this article would be beneficial for graduate students doing research for training and development programs or for instructional design program students. This is also a great article for professors who teach management education.
The University of St. Francis recently launched a new program in the area of talent development and training. The M.S. in Talent Development is an online program – 10 courses – to earn a Master’s degree.
Contact Dr. Bonnie J. Covelli for more information. bcovelli@stfrancis.edu or 815-740-5071
M.S. in Talent Development – Things Have Changed and So Have We
Embrace the future with a M.S. in Talent Development from University of St. Francis, Joliet, Illinois. The new curriculum aligns with the Association for Talent Development (ATD) Talent Development Capability Model™. If you have earned the distinguished Certified Professional in Talent Development (CPTD®) or Certified Professional in Learning and Performance (CPLP®), then you only need nine courses to earn the degree because you can earn credit for prior learning. #ATDmember
The Talent Development program offers employment possibilities such as a talent development manager or director, human resources manager or director, learning and development manager or director, training or education manager or director, manager of organizational learning, employee relations manager, HR administration director, human resources operations manager, development manager, education director, learning manager, staff training and development manager, training and development coordinator, training and development director, training director, training manager, director or dean of continuing education, higher education administration, director of adult or community education, human performance consultant, trainer, consultant, instructional designer.
Students will find both personal and professional growth in the study of talent development. In this program, students have the opportunity to complete assignments they can apply to their organization, institution, or place of employment. They will gain hands-on experience with effective ways of building organizational capability practices including the design, delivery, management, assessment of talent development initiatives uniquely suited to adults. The Talent Development program supports students if they want to move up in their current organization, secure a position in another organization, or make a career change.
The talent development program provides employers with professionals who have expertise in the areas of human resources and learning and development. Students will understand how developing a learning organization leads to improved performance in the workplace, and they will have an awareness of internal and external environments that will enable them to position talent effectively within their organizations.
Program Mission
The Master of Science in Talent Development program provides quality educational experiences in an applied curriculum for professionals in the fields of talent development, human resources, and the delivery of programs for adults.
Program Outcomes
Upon completion of the program, students will be able to:
Increase knowledge of organizational capability practices including the design, delivery, management, assessment of talent development initiatives uniquely suited to adults
Develop professional capability and awareness of ethical practices in the field of talent development
Consult with various talent development stakeholders while building personal capability in the area of lifelong learning
This post is provided to you by genial and gracious guest blogger, Daniel Liestman, graduate student at the University of St. Francis in Joliet, MS in Training and Development program.
Before seeking to incorporate AI into training, one must first consider how to engage with AI in the design process itself. AI can assist in conducting and assessing the learning needs analysis. AI can create eLearning course outlines as well as build content. AI can also assist in writing introductions, crafting transitions, or crafting conclusions. AI can also generate Level 1 and 2 activities and quizzes. AI generated visuals can also be quite engaging! Beyond design, AI can evaluate instructional design content. AI to stays current with the latest trends in instructional design.
Most TD blogs on AI consider incorporating it into training. This blog realizes this is not the goal. Numerous examples are offered which will make the most of free AI sites and tools. This blog is iterative and provides important background information from previous entries to make for a more complete learning experience. At the same time, none of these tools are fool proof. Chat GPT3.5 is offered as a tool for summarizing a discussion and acknowledges some light proof-reading may be needed. Light-proofing—HA! Last time I tried it to summarize, I got nonsense reduced to gibberish.
This post is provided by guest blogger, Sejdije Fejza, graduate student at the University of St. Francis in Joliet, MS in Training and Development program.
In this article, researchers from the University of Queensland in Australia analyzed whether LMS data is useful in understanding learners and their needs. Video based learning management systems were assessed by monitoring how many times a student clicked on a video and the amount of time that video played. Exam results were also reviewed to determine whether LMS data can assist student learning. First, it revealed students’ preferences for learning. Additionally, students can reference back information or work on their own time. They also revealed that shorter videos and content receive the best results when instructing through this LMS.
This source is helpful for organizations who are deciding what factors to assess in their LMS to support student learning. If individuals adopt this form of analysis to support learning, it is important that they carefully choose the best LMS features to assess. This will avoid limitations in data. For instance, it’s important to consider how engaged students are when watching a video. Therefore, the number of times clicked on a video may not necessarily correlate to whether the viewer is actively paying attention to the video to assist in their learning.
Reference
Maloney, S., Axelsen, M., Galligan, L., Turner, J., Redmond, P., Brown, A., Basson, M., & Lawrence, J. (2022). Using LMS log data to explore student engagement with coursework videos. Online Learning, 26(4), 399–423.
This post is provided by guest blogger, Theresa Anderson, graduate student University of St. Francis, MS Training and Development program.
This article on the healthcare education micro-learning environment measure (HEMLEM) is a research article aimed at creating an evidence-based measurement tool for assessing clinical micro-learning environments across several healthcare professional student groups. The authors suggest there may be gaps between what healthcare professional students should be learning and what they learn. The authors took a mixed methods approach to create a micro-learning environment measure. They acknowledge that teaching quality, staff attitudes, and behaviors are critical for a good micro-learning environment.
The article is helpful for anyone attempting to measure how micro-learning within the education of a healthcare professional environment affects students’ learning. The authors created a measurement tool through a step-wise approach: literature analyzing existing tools, generating new items through thematic analysis of student experiences, the Delphi process involving healthcare educators, piloting the prototype, and item reduction. The item reduction tool was a twelve-question survey of the students with differing healthcare professions. HEMLEM seems to be an efficient way to measure success or what needs to be improved in a micro-learning environment.
References
Isba, R., Rousseva, C., Wolf, K., & Byrne-Davis, L. (2020). Development of a brief learning environment measure for use in healthcare professions education: The healthcare education micro learning environment measure (HEMLEM). BMC Medical Education, 20(110). https://doi.org/10.1186/s12909-020-01996-8
This post is provided by guest blogger, Debra Eungard, a graduate student at the University of St. Francis in Joliet, MS in Training and Development program.
Online learning vs face to face training by Georgina Cooke (2023) is a thought-provoking article. In the article, Ms. Cooke (2023) discusses the difference between online learning compared to face-to-face learning and goes on to discuss a blended model. She digs into the notion that today’s workforce leans toward online design. Ms. Cooke (2023) gives the reader advantages to online learning that are beneficial to both the company and the employee involved with the training. She concludes the article by expounding on the benefits of a blended program. She advises the reader that there are strategies and approaches that can make the blended model the most attractive for all involved.
The article is an interesting read for both the training department and the employee in that it brings to the forefront the difference between all the different models. Ms. Cooke (2023) gives clear and concise definitions with tips and strategies that can be implemented. From the organization’s perspective, this article can be useful when organizing or creating content for remote training, face-to-face, or a blended model. It allows them to research which model fits their staff’s needs. This article can also be helpful for the remote staff going through the training. The author explains the importance of all three methods and makes it easy to understand why a company moves towards one approach compared to the other models.
This post is provided by guest blogger, Sejdije Fejza, graduate student at the University of St. Francis in Joliet, MS in Training and Development program.
In this article published by Society for Human Resource Management, Nicole Lewis (2022) explains that one inhibitor of employee retention is the employee not achieving a sense of growth in the workplace. Additionally, the pandemic promoted quantity of training. However, employees are looking for quality and relative purpose. Lewis (2022) presents the solution of alignment. This means that learning designers should first identify the performance gaps within the company or individual employee. Once needs are identified, the trainer should work to keep learning related to those needs through other technological strategies such as virtual reality and contextually relevant platforms such as YouTube.
Individuals will find this article useful if they are teams who are researching best practices in learning strategies. Others include institutions or designers who may have already provided too many resources and are now looking to decrease learning inventory in the efforts to become more aligned. This source originated from the Society of Human Resource Management which is a source used by many in the field to retain their employees or refer to laws and other information relating to human resources and employee development.
This post comes to you courtesy of your convivial and continually-learning guest blogger, Daniel Liestman a master’s degree student in the Training and Development program at the University of St. Francis (Joliet, IL).
Moore & Klein (2020) accept that most learning in the workplace is informal, but realize the bulk of resources are provided for formal training. In a survey (N=385) and subsequent interviews (n=20) of trainers they found T&D professionals engage in informal learning to foster informal learning by passing along articles or link to targeted individuals. Trainers also supply just-in-time job aids and tools. In addition, they create and curate learning objects and related materials for just-in-case situations. Alternatives not explored might include brown bag sessions or walking about and engaging with staff. Fostering informal leaning is a resource-efficient approach to counter budget and staffing shortfalls while improving organizational performance.
IMHO (in my humble opinion), Moore & Klein (2020) address an intriguing topic. The rub is that the suggestions in the survey and those offered in the interviews are pedestrian (email, help sheets, filing away digital objects, etc.) How might technology be better deployed? How might online organizations foster those watercooler moments? Could corporate maker-spaces foster creativity and discovery to grow the bottom line? How can informal learning be tracked and evaluated? The profession seems to have a wing-and-a-prayer approach to informal learning. The research would have been more satisfying had the authors dug more. I do hope this is not as deep as they could go, and this is all that they can offer. Perhaps these topics can be pursued in subsequent research?
USF Training 