Academic System Resource Planning (ASRP)


Nile University is a member and a technical coordinator of an EU funded project through Erasmus+KA2 CBHE scheme called “Academic System Resource Planning (ASRP)”, which is a fully automated Smart Campus. 

The project is a partnership between Nile University (NU), Ain Shams University (ASU), Suez Canal University (SCU), Aswan University (ASWU), Ministry of Higher Education (MOHE), National Authority for Quality Assurance and Accreditation (NAQAAE) from Egypt, Royal Institute of Technology (KTH) from Sweden, University of Oviedo (UNIOVI) from Spain, Staffordshire University (STAFFU) from UK and European Quality Assurance Agency (EQAA) from Germany.




Objective and Scope

The project aims at creating a quality-tailored ICT-based smart automated academic and administrative university environment, infiltrating the global perspective of quality assurance and the best practices for university management within the HE system in EG. This is done through the design and development of a smart digital platform for monitoring, analysis and control of internal processes; thus, allowing for transparency, efficient management of human and capital resources, fact-based decision making, yielding an HEI model with education quality KPIs being the controlling metrics for its automated processes, and rendering education quality an INHERENT feature in all actions occurring within.

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Interactive ASRP Module Map

The proposed automated system starts with identification of the inputs, outputs and procedures of all academic and administrative processes and quantification of performance metrics along with the KPIs and associated Education Quality criteria to be compatible with the proposed automatic control algorithm for university automation. A set of university-wide control variables are defined, which influence the performance of each and every process within the HEI.

Processes such as academic, administrative, stakeholders' relations, student affairs, Quality Assurance and university management decision making are fully computerized and programmed with inputs, outputs and performance metrics that are used in a feedback closed-loop control to map against model values prescribed by the national Quality Assurance criteria and KPIs for Best Practice models. Any deviation in the performance metrics is spotted automatically and corrective actions are either taken autonomously, or via HEI decision making system to close this gap. Via the proposed system, HEI management shall have instantaneous access to the current quality-tailored performance within the institution, allowing for fast, fact-based decision making. Quality Assurance authority shall have a real-time remote visual access to the Quality-based KPIs at the participating EG HEIs.

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Public Dashboard for Real-time Measurements