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Model . 2025
License: CC BY
Data sources: Datacite
ZENODO
Model . 2025
License: CC BY
Data sources: Datacite
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Digital Information Transfer Cycle for Academic Videos

Digital Information Transfer Cycle
Authors: Prethika Acharjee;

Digital Information Transfer Cycle for Academic Videos

Abstract

This document presents a comprehensive theoretical framework explaining how academic video content is created, stored, disseminated, retrieved, used, evaluated, and updated within digital learning environments. Drawing from Lancaster’s (1978) Information Transfer Cycle, the study adapts the model to modern digital ecosystems. This also distinguishes between born-digital and made-digital (digitized) academic videos and analyzes how information flow differs between these two formats. It argues that born-digital content demonstrates greater efficiency, richer metadata, smoother dissemination, and stronger preservation potential, whereas made-digital content faces challenges related to digitization quality, metadata reconstruction, and long-term sustainability. A major contribution of the study is its detailed, stage-wise model of the digital information transfer cycle for academic videos, comprising eight stages: Creation and authorship, storage and organization, transmission and dissemination, search and retrieval, utilization and learning, feedback and updating, evaluation, course revision and new content creation. The document also addresses the emerging issue of AI-generated academic videos, clearly establishing that authorship remains human-centered, as AI systems lack legal and intellectual agency. This position is supported by international copyright and LIS standards. At a macro level, the study situates academic video flow within a global knowledge ecosystem involving Learning Management Systems (LMS), Content Delivery Networks (CDNs), Open Educational Resource (OER) repositories, metadata aggregators, and recommendation algorithms. It highlights the role of metadata standards, classification systems, indexing methods, and AI technologies in enhancing discoverability, accessibility, and learning outcomes. Overall, the document provides a theoretically grounded, well-structured, and policy-relevant analysis of digital academic video dissemination, offering a unified model useful for researchers, educators, librarians, instructional designers, and platform developers.

Keywords

FOS: Computer and information sciences, CDN, Information Science/methods, Artificial intelligence, Information Management, Metadata/trends, Information exchange, Information Dissemination/methods, Information Theory, Lancaster Model, Information Storage and Retrieval, Database Management Systems/classification, Information Science/standards, Artificial Intelligence/standards, Information transfer, Social psychology, Digital Divide, Database Management Systems/trends, Information, Scientific and technical information, Psychology, Database Management Systems/standards, Video Content, Information network, Information Science, Personnel Staffing and Scheduling Information Systems, Digital Technology, Computer and information sciences, Libraries, Digital, Information Storage and Retrieval/classification, Personnel Staffing and Scheduling Information Systems/classification, FOS: Psychology, Information Retrieve, Metadata parameters, Artificial Intelligence/classification, Information Science/organization & administration, Digital Technology/classification, Information Technology, Information infrastructure, Technical information, Analog-Digital Conversion, Information Science/classification, psychology, Information system, Preventive information, Cognitive learning, Digital Technology/education, Databases, academic video, Artificial Intelligence, Artificial Intelligence/trends, Internet protocols, Taxonomy, Metadata, Information Storage and Retrieval/methods, Information Dissemination, Metadata/classification, Information Storage and Retrieval/trends, Information service, ITC, folksonomy, Information Science/education, LMS, Artificial Intelligence/supply & distribution, Information Transfer Cycle, Born Digital, Metadata/standards, AI, ICT, Literacy/psychology, Database Management Systems, Selective dissemination of information, Digital Technology/methods, TCP/IP

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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