PSY-6422

Lee, Y.-M., Jahnke, I., & Austin, L. (2021). Mobile microlearning design and effects on learning efficacy and learner experience. Educational Technology Research & Development, 69(2), 885–915.
This article summarizes the results of a study that examined microlearning methods and how learner motivation was impacted.

Lohman, L. (2024). How can you deliver microlearning when learners don’t want it? Designing microlearning for socially oriented learners. Educational Technology & Society, 27(1), 147–165.
This article looks at the challenges of using microlearning when the audience is not receptive to the methods.

Passalacqua, M., Pellerin, R., Yahia, E., Magnani, F., Rosin, F., Joblot, L., & Léger, P.M. (2024). Practice with less AI makes perfect: Partially automated AI during training leads to better worker motivation, engagement, and skill acquisition. International Journal of Human-Computer Interaction.
This source provides the results of a study on the impact of AI on training, including the effects on motivation and employee engagement.

Puah, S., Bin Mohmad Khalid, M. I. S., Looi, C. K., & Khor, E. T. (2021). Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance. Frontiers in Psychology, 12.
This article summarizes research on workers’ intent and training, including the use of microlearning strategies and motivation.

Siminovich, C. (2021). Modernize training with AI, XR, and microlearning. Chemical Engineering Progress, 117(5), 44–47.
This article summarizes how new AI tools can be incorporated with training to maximize skill development in the digital age.