The Learning Analytics Value Chain

A persistent challenge for the learning analytics community is how to achieve a meaningful impact on educational practice. This paper proposes that Porter’s Value Chain framework provides a useful lens for addressing this challenge. This study developed operational definitions of a Learning Analytics Value Chain and mapped learning analytics research output (3,720 publications) over the last 16 years to its five stages: 1. Concept Development, 2. Prototyping & Efficacy, 3. Evaluation, 4. Dissemination, and 5. Impact & Iteration. SoLAR supported learning analytics venues show heavy concentration in Prototyping & Efficacy (41.5-43.2%) and Evaluation (43.4-53.4%), with minimal Dissemination (0.1-3.8%) and Impact & Iteration (2.8-6.1%) research. Non-SoLAR supported research demonstrates a slightly more balanced distribution, specifically, higher Concept Development (22.5% vs. 0-6.7%) and Dissemination (9.0% vs. 0.1-3.8%) emphasis. These findings suggest that achieving impact has been hampered by insufficient research examining how innovations reach educators. The 470-fold difference between evaluation (46.7%) and dissemination research (0.1%) represents a critical missing piece of the research landscape. The field has developed strong technical capabilities while neglecting implementation science and scaling strategies. Addressing the impact gap requires portfolio re-balancing toward dissemination research, longitudinal studies, and theoretical development rather than continued technical emphasis alone.