Extending Cognitive Load Theory: The CLAM Framework for Biometric, Adaptive, and Ethical Learning

Cognitive Load Theory (CLT) and the Cognitive Theory of Multimedia Learning (CTML) have long served as foundational frameworks in instructional design. However, their applicability to contemporary, technologically mediated learning environments remains under-theorized. This review critically examine...

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Main Authors: Eleni Vasilaki, Aristea Mavrogianni
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Psychology International
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Online Access:https://www.mdpi.com/2813-9844/7/2/40
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author Eleni Vasilaki
Aristea Mavrogianni
author_facet Eleni Vasilaki
Aristea Mavrogianni
author_sort Eleni Vasilaki
collection DOAJ
description Cognitive Load Theory (CLT) and the Cognitive Theory of Multimedia Learning (CTML) have long served as foundational frameworks in instructional design. However, their applicability to contemporary, technologically mediated learning environments remains under-theorized. This review critically examines CLT and CTML, focusing on their assumptions, empirical contributions, and current limitations in addressing the complexities of dynamic, AI-enhanced educational settings. The discussion is further enriched through engagement with complementary perspectives, including self-regulated learning, dual process theory, and connectivism. These frameworks illuminate conceptual convergences but also expose theoretical tensions, particularly regarding unresolved constructs such as germane cognitive load and the methodological challenges associated with real-time cognitive load measurement. In response to these gaps, this paper proposes the Cognitive Load-Aware Modulation (CLAM) strategy—a conceptual model designed to extend cognitive load principles in adaptive, ethically responsive learning environments. Synthesizing insights from cognitive psychology, educational technology, and affective computing, CLAM supports the design of personalized, data-driven instructional systems attuned to learners’ cognitive and emotional states. The model emerges not merely as a theoretical contribution, but as a future-oriented framework rooted in the critical synthesis of the reviewed literature. Its practical applications for real-world educational settings are outlined, and its empirical validation constitutes the next phase of our ongoing research project.
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spelling doaj-art-5e53a7dc709c454fabe7734ae60c4f612025-08-20T03:16:38ZengMDPI AGPsychology International2813-98442025-05-01724010.3390/psycholint7020040Extending Cognitive Load Theory: The CLAM Framework for Biometric, Adaptive, and Ethical LearningEleni Vasilaki0Aristea Mavrogianni1Department of Education, School of Education, University of Crete, 74100 Rethymno, GreeceDepartment of Education, School of Education, University of Crete, 74100 Rethymno, GreeceCognitive Load Theory (CLT) and the Cognitive Theory of Multimedia Learning (CTML) have long served as foundational frameworks in instructional design. However, their applicability to contemporary, technologically mediated learning environments remains under-theorized. This review critically examines CLT and CTML, focusing on their assumptions, empirical contributions, and current limitations in addressing the complexities of dynamic, AI-enhanced educational settings. The discussion is further enriched through engagement with complementary perspectives, including self-regulated learning, dual process theory, and connectivism. These frameworks illuminate conceptual convergences but also expose theoretical tensions, particularly regarding unresolved constructs such as germane cognitive load and the methodological challenges associated with real-time cognitive load measurement. In response to these gaps, this paper proposes the Cognitive Load-Aware Modulation (CLAM) strategy—a conceptual model designed to extend cognitive load principles in adaptive, ethically responsive learning environments. Synthesizing insights from cognitive psychology, educational technology, and affective computing, CLAM supports the design of personalized, data-driven instructional systems attuned to learners’ cognitive and emotional states. The model emerges not merely as a theoretical contribution, but as a future-oriented framework rooted in the critical synthesis of the reviewed literature. Its practical applications for real-world educational settings are outlined, and its empirical validation constitutes the next phase of our ongoing research project.https://www.mdpi.com/2813-9844/7/2/40cognitive load theory (CLT)multimedia learningadaptive technologiespersonalized educationCLAM strategy
spellingShingle Eleni Vasilaki
Aristea Mavrogianni
Extending Cognitive Load Theory: The CLAM Framework for Biometric, Adaptive, and Ethical Learning
Psychology International
cognitive load theory (CLT)
multimedia learning
adaptive technologies
personalized education
CLAM strategy
title Extending Cognitive Load Theory: The CLAM Framework for Biometric, Adaptive, and Ethical Learning
title_full Extending Cognitive Load Theory: The CLAM Framework for Biometric, Adaptive, and Ethical Learning
title_fullStr Extending Cognitive Load Theory: The CLAM Framework for Biometric, Adaptive, and Ethical Learning
title_full_unstemmed Extending Cognitive Load Theory: The CLAM Framework for Biometric, Adaptive, and Ethical Learning
title_short Extending Cognitive Load Theory: The CLAM Framework for Biometric, Adaptive, and Ethical Learning
title_sort extending cognitive load theory the clam framework for biometric adaptive and ethical learning
topic cognitive load theory (CLT)
multimedia learning
adaptive technologies
personalized education
CLAM strategy
url https://www.mdpi.com/2813-9844/7/2/40
work_keys_str_mv AT elenivasilaki extendingcognitiveloadtheorytheclamframeworkforbiometricadaptiveandethicallearning
AT aristeamavrogianni extendingcognitiveloadtheorytheclamframeworkforbiometricadaptiveandethicallearning