The Impact of AI-Driven Application Programming Interfaces (APIs) on Educational Information Management

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) powe...

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Vydané v:	Information (Basel) Ročník 16; číslo 7; s. 540
Hlavní autori:	Pérez-Jorge, David, González-Afonso, Miriam Catalina, Santos-Álvarez, Anthea Gara, Plasencia-Carballo, Zeus, Perdomo-López, Carmen de los Ángeles
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.07.2025
Predmet:	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
ISSN:	2078-2489, 2078-2489
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Abstract	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.
AbstractList	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.
Audience	Academic
Author	González-Afonso, Miriam Catalina Plasencia-Carballo, Zeus Perdomo-López, Carmen de los Ángeles Pérez-Jorge, David Santos-Álvarez, Anthea Gara
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SubjectTerms	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
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Title	The Impact of AI-Driven Application Programming Interfaces (APIs) on Educational Information Management
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