Assessing Cognitive Load and Managing Extraneous Load to Optimize Training
Abstract
Abstract -- Approved for Public ReleaseIn adaptive training, real-time assessment of attentional states, such as mental workload offers the potential to identify when extraneous cognitive load or lack of engagement with materials might be having deleterious effects on learning. Such an approach would have high value in military training contexts. However, recognizing overload or inattention alone is insufficient if this cannot be linked to immediate changes in the approach to instruction. This research will examine how todynamically couple measures of cognitive workload and attentional engagement with the augmented reality head-mounted display that can deliver Navy-relevant training materials via visual integration of information into the systems and operations being learned. We propose physiological measurement of workload and attentional states. This offers the potential to advance the underlying science necessary to optimize learning, reduce training costs, and improve the performance of future Navy personnel.In the proposed program ofresearch, we will address the current challenges of supplying integrated yet adaptable instructional materials and coupling these with real-time assessment of the cognitive load. Our proposed research has an overarching goal of integrative, adaptable, and responsive training, with a focus on the effectiveness of attention-related principles of cognitive-load theory in instruction and long-term retention as supported by AR-HMD technology, and physiological measurement of engagement and cognitive load.Our proposed experimental approach will have three thrusts, related to (1) mental workload, desirable difficulties, and intrinsic load, (2) engagement in sources of germane versus extraneous load, and (3); the inherent properties of the AR-HMD to provide linking. All three thrusts willexamine convergent measures of learning outcome and physiological measures as influenced by experimental manipulations designed to influence those learning outcomes.The resulting research project will provide the basis for how to exploit the unique properties of the AR-HMD to optimize the cognitive load of instruction.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 24, 2023
- Source ID
- N000142312298
Entities
People
- Francisco Ortega
Organizations
- Colorado State University
- Office of Naval Research
- United States Navy