AR enhanced analytics as a constructivist-, experiential-, and cognitively-grounded integration of AR technology with learning analytics¶

Theory · All theories
Evidence · 5 claims (4 for, 1 mixed) · 1 study (1 review), q3 · 0 of 1 report an effect size · 5 claims rest on one study

Description¶

The review frames AR enhanced analytics as the systematic collection, analysis, and interpretation of data from AR interactions in learning environments, grounded in constructivist, experiential, situated/embodied, and cognitive theories (CTML, CLT). It builds on the Kazanidis et al. (2021) AR-LA model that "explicitly integrates AR technology with LA to systematically measure learner interactions, enabling personalized feedback and interventions." The framework distinguishes AR itself from AR enhanced analytics, which focus on extracting and using interaction data to optimize effectiveness and personalize learning.

Design Implications¶

Context¶

Requirements¶

• AR applications must capture data from learner interactions with AR content (engagement with virtual objects, navigation, responses to stimuli) for analytics to be generated

Constraints¶

• The review notes some AR features are not exclusive to AR, as they are found in other systems like ubiquitous and mobile learning environments

Target Learners¶

• primary school students
• secondary school students
• higher-education students

Target Learning Objectives¶

• understanding student engagement, motivation, behaviour, learning experiences, and acquisition of skills

Claims¶

• Ar Analytics Effectiveness Tracking Interaction Most Reported [+M]
• The most frequently reported affordances of AR enhanced analytics are interaction, projection of contextual information, and sensory capability [+W]
• Reported limitations of AR enhanced analytics include cognitive overload from immersive environments, technological constraints, usability challenges, and inconsistent measurement approaches [~W]
• A tablet-based AR app displaying real-time measurement data above circuit components aided conceptual knowledge acquisition more effectively than traditional physics lab lessons [+W]
• Students using an AR system for plant study showed higher learning motivation than a control group [+W]

Related Theories¶

• Constructivist prescriptive principles for learning environments
• Activity theory frames human activity as a system of six interacting elements (subject, object, tools, community, rules, division of labor)

Examples¶

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Key Sources¶

• Manjeet Singh Usma, Shaun Bangay and Atul Sajjanhar. (2025). Augmented Reality Enhanced Analytics for Education: A Systematic Review. Journal of Learning Analytics 12(3). https://doi.org/10.18608/jla.2025.8447