JISC

Overview

Intelligent Decision Support (IDS) is key to the effective management of HE institutions. All institutions have multiple data sources that contain valuable information that must be integrated and processed to inform the key business processes. Currently, there are many technical, legal and organisational challenges that must be addressed in HE in order to make IDS effective.

Economic and quality factors are placing increasing demands for speedy and accurate decision-making using a variety of sources of information with HE. Areas such as recruitment, course management, student support and institution management all have scope for improvement through the intelligent use of existing data.

The following challenges need to be addressed to achieve IDS in HE

• There is currently no analysis of the (technical, legal, logistical) requirements of HE stakeholders for IDS. Further, there is no forum where interested parties can share requirements and solutions for IDS. 
• No analysis has been made of existing commercial solution providers in terms of working with them to provide economic sector-wide solutions where possible. 
• There is no roadmap for improvement in decision making within HE. Such a roadmap can be used to strategically plan and target improvements available as shared services.

The team at TVU has been working on a JISC funded MCMS project that uses Data Mining technology to detect and improve issues related to student retention. The project has addressed some of the issues outlined above which makes TVU ideally placed to manage and contribute to an initiative through the FSD programme that addresses the challenges outlined above.

Aims and objectives

The aim of the project is to set up an IDS-SIG. The proposed IDS STG will identify areas where decision support can be improved across the sector and will propose opportunities for best practice and integration with short to medium terms benefits and will propose a roadmap which will maximise current investment and inform future investment in this area.

The proposed IDS SIG will engage with key institutional stakeholders and across the sector in order to build a comprehensive statement of IDS requirements for areas where decision support can be improved, leading to a sector-wide IDS roadmap, which will maximise current investment and inform future investment in this area.

The project will produce the following outcomes

• Requirements for IDS in HE 
• Guidelines and a best practice report
• Integration opportunities in the short and medium term
• A roadmap to inform future investment in the sector
• A repository of IDS information

Project methodology

The proposed IDS SIG will engage with key institutional stakeholders and across the sector in order to build a comprehensive statement of IDS requirements for areas where decision support can be improved, leading to a sector-wide IDS roadmap, which will maximise current investment and inform future investment in this area. This will take the form of a set of workshops some with HE institution members others with suppliers. The engagement will be in form of workshop, interviews and questionnaires.

Anticipated impact

The project will have the potential to contribute in the following institutional context areas: 

Academic and administrative areas

• Monitoring student progress in real-time and propose intervention activities
• Construct both general and specific guidelines relating to student problems
• Produce flexible and detailed information to be used at progression and award boards
• Identify patterns in student recruitment to support recruitment policies and activities
• Support course validation processes by allowing institution regulations to be automated
• Support institutional change by encoding and monitoring strategic goals and policies

Level of cultural readiness and technical maturity

The MCMS project has shown that data integration and data mining is a key enabling technology for IDS and early results from this project have shown that these activities are tractable. Extensive requirements engineering with IDS stakeholders within the MCMS project has shown that here is a strong desire within decision making bodies (such as examination boards, course validation boards etc) for flexible and integrated access to institutional data. 

Known integration issues

Early results from the MCMS project has identified a number of key integration issues that the sector should be aware of including:

• Legal issues relating to data protection
• Organisational culture relating to the ownership of data
• Data integration can be addressed using model driven technologies