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The Impact of AI-Driven Application Programming Interfaces (APIs) on Educational Information Management
by
González-Afonso, Miriam Catalina
, Plasencia-Carballo, Zeus
, Perdomo-López, Carmen de los Ángeles
, Pérez-Jorge, David
, Santos-Álvarez, Anthea Gara
in
Academic achievement
/ Adaptation
/ Algorithms
/ Application programming interface
/ application programming interfaces (APIs)
/ Applications programming
/ Artificial intelligence
/ artificial intelligence in education
/ automated feedback
/ Automation
/ Chatbots
/ Collaboration
/ Computational linguistics
/ Customization
/ Education
/ educational data analytics
/ Educational evaluation
/ Educational technology
/ Ethics
/ Feedback
/ Generative artificial intelligence
/ Information management
/ Interoperability
/ Knowledge management
/ Language processing
/ Learning
/ Learning management systems
/ Machine learning
/ Natural language interfaces
/ Neural networks
/ Pedagogy
/ Personalized learning
/ Real time
/ Systematic review
/ Teaching
/ Tutoring
2025
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The Impact of AI-Driven Application Programming Interfaces (APIs) on Educational Information Management
by
González-Afonso, Miriam Catalina
, Plasencia-Carballo, Zeus
, Perdomo-López, Carmen de los Ángeles
, Pérez-Jorge, David
, Santos-Álvarez, Anthea Gara
in
Academic achievement
/ Adaptation
/ Algorithms
/ Application programming interface
/ application programming interfaces (APIs)
/ Applications programming
/ Artificial intelligence
/ artificial intelligence in education
/ automated feedback
/ Automation
/ Chatbots
/ Collaboration
/ Computational linguistics
/ Customization
/ Education
/ educational data analytics
/ Educational evaluation
/ Educational technology
/ Ethics
/ Feedback
/ Generative artificial intelligence
/ Information management
/ Interoperability
/ Knowledge management
/ Language processing
/ Learning
/ Learning management systems
/ Machine learning
/ Natural language interfaces
/ Neural networks
/ Pedagogy
/ Personalized learning
/ Real time
/ Systematic review
/ Teaching
/ Tutoring
2025
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Do you wish to request the book?
The Impact of AI-Driven Application Programming Interfaces (APIs) on Educational Information Management
by
González-Afonso, Miriam Catalina
, Plasencia-Carballo, Zeus
, Perdomo-López, Carmen de los Ángeles
, Pérez-Jorge, David
, Santos-Álvarez, Anthea Gara
in
Academic achievement
/ Adaptation
/ Algorithms
/ Application programming interface
/ application programming interfaces (APIs)
/ Applications programming
/ Artificial intelligence
/ artificial intelligence in education
/ automated feedback
/ Automation
/ Chatbots
/ Collaboration
/ Computational linguistics
/ Customization
/ Education
/ educational data analytics
/ Educational evaluation
/ Educational technology
/ Ethics
/ Feedback
/ Generative artificial intelligence
/ Information management
/ Interoperability
/ Knowledge management
/ Language processing
/ Learning
/ Learning management systems
/ Machine learning
/ Natural language interfaces
/ Neural networks
/ Pedagogy
/ Personalized learning
/ Real time
/ Systematic review
/ Teaching
/ Tutoring
2025
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The Impact of AI-Driven Application Programming Interfaces (APIs) on Educational Information Management
Journal Article
The Impact of AI-Driven Application Programming Interfaces (APIs) on Educational Information Management
2025
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Overview
In today’s digitalized educational landscape, the intelligent use of information is essential for personalizing learning, improving assessment accuracy, and supporting data-driven pedagogical decisions. This systematic review examines the integration of Application Programming Interfaces (APIs) powered by Artificial Intelligence (AI) to enhance educational information management and learning processes. A total of 27 peer-reviewed studies published between 2013 and 2025 were analyzed. First, a general description of the selected works was provided, followed by a breakdown by dimensions in order to identify recurring patterns, stated interests and gaps in the current scientific literature on the use of AI-driven APIs in Education. The findings highlight five main benefits: data interoperability, personalized learning, automated feedback, real-time student monitoring, and predictive performance analytics. All studies addressed personalization, 74.1% focused on platform integration, and 37% examined automated feedback. Reported outcomes include improvements in engagement (63%), comprehension (55.6%), and academic achievement (48.1%). However, the review also identifies concerns about privacy, algorithmic bias, and limited methodological rigor in existing research. The study concludes with a conceptual model that synthesizes these findings from pedagogical, technological, and ethical perspectives, providing guidance for more adaptive, inclusive, and responsible uses of AI in education.
Publisher
MDPI AG
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