iFEST 2022 Summary
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The Innovation, Instruction, and Implementation in Federal e-Learning Science & Technology (iFEST) Conference is an ideal conference to keep training and education organizations up to date on the state-of-the-art learning practices and procedures related to learning with technology. The conference is “the premier conference on distributed learning, bringing together thought leaders, innovators, and senior officials from government, industry, and academia to collaborate and share the latest challenges and innovations in the field” (Advanced Distributed Learning Initiative, 2021). The conference first started in 2003, and the 2022 iFEST was the 19th successful annual conference. The conference is jointly organized by the National Training and Simulation Association and the Advanced Distributed Learning Initiative. It is normally held around the end of August or early September. The conference offers innovative keynote talks, panel sessions, interactive activities, exhibits by industry, and talks from individual presenters. Topic areas include digital learning science, learning technology, learning data, technology interoperability, policy, and a timely topic that changes annually such as training and learning in the new normal.
In 2022, the conference returned to an in-person event held in Washington, D.C. The conference had attendees that spanned the public, private, nonprofit, and academic sectors. The bulk of the attendees were from the federal government/ military backgrounds, who received free attendance to the conference. This year’s keynote speakers were Shawnna Hoffman, chief technology leader, legal strategy, and operations for Dell Technologies; and Beverly J. Seay, southeast regional director for the National Security Innovation Network (Advanced Distributed Learning Initiative, 2022). The 2022 conference included 45 individual talks and 13 poster presentations covering cutting-edge best practices, examples, and research on the aforementioned topics.
We present four papers as examples from the conference. The current special issue solicited submissions from the accepted talks and posters. Submitted papers were independently peer reviewed by members of the Journal of Military Learning. Craig et al.’s paper (2023) presents an empirical evaluation of the PERvasive Learning System, which shows evidence for real-world impact in an Army schoolhouse. Goodell and Schatz (2023) provide a high-level overview of the transdisciplinary area of learning engineering, which combines the science of learning, systems engineering, and human-centered design areas to build learning systems that work with learners. Rude (2023) provides best practices for learning ecosystems to foster distributed learning focusing on forming the stakeholder ecosystem, assessing stakeholder relationship health, and maintaining stakeholder networks. Kurzweil et al. (2023) provides an overview of best practices for fostering partnerships that can support distributed learning within military education.
References
Advanced Distributed Learning Initiative. (2021). iFEST 2021 call for ideas. https://adlnet.gov/news/2021/01/15/iFEST-2021-Announcements/
Advanced Distributed Learning Initiative. (2022). iFEST 2022 wrap-up new paradigm of learning: Partner and prevail. https://adlnet.gov/news/2022/09/20/iFEST-Wrap-Up/
Craig, S. D., Riddle, D. L., Lauer, S., Hughes, G. I., Elmore, W. R., Udell, C. E., Murphy, J. S., & Milham, L.M. (2023). Investigating the impact of mobile microlearning and self-regulated learning support on soldiers’ efficacy and retention within an Army schoolhouse. Journal of Military Learning, 7(1).
Goodell, J., Kessler, A., & Schatz, S. (2023). Learning engineering at a glance. Journal of Military Learning, 7(1).
Kurzweil, D., Macaulay, L., & Marcellas, K. (2023). The holy grail of developing partnerships for DL in military education: The keys to success. Journal of Military Learning, 7(1).
Rude, D. A. (2023). Learning ecosystems: Forging stakeholder partnerships to fuel optimal advanced distributed learning practices. Journal of Military Learning, 7(1).
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