Assessment Task

 

LO’s	Module learning outcomes covered by this task (from the Module descriptor)
1	Effectively apply a method of capturing and specifying user and system requirements.

 

 

Guidelines and background to the assessment
Hand in date		Assessment type
Question 1 (40 marks)   The Unite Nations have decided to come out with an e-agricultural roadmap for all countries. EU and other countries have taken the lead in coming out with strategies and documentation to rollout their pilot projects.   The government of Ghana have decided to undertake a national project in building an effective and efficient e-agriculture structures and mechanisms for extension, surveillance and early warnings.   The agriculture sector in Ghana holds great potentials to transform the poor unto a sustained economic growth pathway. The need to enhance productivity and incomes of both smallholder family farmers as well as that of commercial farmers is key to promoting livelihood empowerment, food and nutrition security as well as making significant contribution to the nation’s Gross Domestic Product (GDP). Poor agricultural practices, inefficient flow of relevant knowledge through extension services and early warning messages on weather patterns, climate related hazards and pest infestations and ineffective supply chains with lack of access to market information are some of the factors militating against the agriculture sector in Ghana. Enhancing the ability of farming communities through robust innovative systems that allows digital and online applications to access financial solutions, knowledge banks, value chain networks, e-commerce, transportation, and logistics management will sustainably catalyse farmers productivity and ensure profitability, food security and employment opportunities.   In Ghana, both the private sector and public sector as well as the farmers with the aid of different NGOs, CSOs have increasingly promoted different Information and Communication technologies (ICTs) with the ultimate goal of addressing some of these problems faced by the agriculture sector. The different significant achievements chalked in the use of ICT in aid of Agriculture sector enhancement, provides the motivational background of this Technical Cooperation Project (TCP) which seeks to holistically coordinate and transit a viable and robust E-agriculture ecosystem. This will also build on Food and Agricultural

 

 

 

Organization’s (FAO) support to Ministry of Food and Agriculture (MoFA) and National Disaster management Organisation (NADMO) in integrating its Agriculture and Early Warning Systems.

 

One of the key technical objectives the government seek to achieve is have all E- agriculture systems harmonized, strengthened for generation and dissemination of data, monitoring & evaluation, surveillance and early warnings, pricing and market information. And also to make the harmonized e-extension and e- services system strengthened for the promotion of commodity value chains and the formalization of informal rural agribusinesses.

 

The ministry of food and Agriculture is tasked to lead the stakeholder team throughout the lifecycle of the project. Other ministries such as the ministry of Health, Finance, education, Environment, Science and technology, communications, National security etc. were also among the stakeholders. This nationwide e-agriculture information system to be built is to enhance better early warning, service delivery and information sharing. The information system has the following capabilities:

· Connect the rural, district and regional farm data in a distributed network environment with data centric capability.

· Provision of platforms where data can be used to determine and assess the efficient delivery of quality of services across the supply chain of agricultural services.

· Enhance smooth patient mobility and tracking of goods and services across geographical areas whilst ensuring secure data exchange.

· Help map diseases across geographical areas with multi-level data analytical capability. This includes the following data sets: weather information, demographic data, socio-economic data, environmental, climate data etc

· Provide a platform where edge, fog and cloud computing capabilities can be rollout to support agricultural service at all levels where such technologies are deployed.

· Give capability for disparate devices and systems across the agricultural supply chain such as mobile device applications, smart devices etc. This is help integrate and support rural farmers and urban farmers seamlessly and to enhance integration and interoperability.

· Enhance interoperability between other systems at other sectors and agencies such as food and drugs board, customs services, ports and harbour agencies etc

· Help the agricultural surveillance and early warning unit to mine real-time data from the information system to rapidly respond to outbreak of diseases and track spread across various farms etc.

· Support the ministries responsible for planning, population and economic activities to engage models that can use agricultural data for national planning in terms of food security, agricultural land use etc.

· Enhance data driven governance for the agricultural sector so that effective national planning and inclusive policy and governance can be carried out efficiently.

 

· To accommodate future interoperability and integrations with other systems via an enterprise service bus.

· Etc.

 

The system should also capture the following information the as part of it

· Farmer’s farm data

· Agricultura research institutions information

· Extension services information on data collected from various farmers in a geographical area

· Veterinary laboratory services and other services

· Local markets and storage houses information systems

· Agricultural training facility information systems

· Farm input suppliers’ information systems

· Etc.

 

The governments of Ghana have future plans of creating web services where individual farmers doing at home can integrate their farm systems to help them have their data integrated. This help collect data on seed performance, disease spreads, etc. The system also will incorporate a large artificial intelligence disease diagnostic system that will help in collection of data across farms whilst collecting data during diagnostics of diseases of various farms.

 

For example, a farmer can use a smartphone to scan a spot on his farm to aid in disease diagnostics and these devices can be using different operating systems that are written in different languages. The system will have future capabilities in supporting other Internet of things-IoT ubiquitous agricultural devices that can easily be hooked up to the system to provide a larger pool of data for analytics and effective data driven agricultural services for farmers.

 

The government also intend to deploy Artificial intelligence federated agriculture computing systems to support the agriculture sector in district where connectivity in terms of internet will be a concern etc. The government intend to deploy blockchain technology as well to ensure accurate agriculture data, tracking, avoidance of fake agricultural inputs such as seeds, fertilizers etc and ensuring authentic usage of agricultural equipment across all sectors.

 

There are plans to also integrate data with international agribusiness and supply chain systems across different geographical areas in exchanging of real-time information on agricultural products and services.

 

The entire agriculture information system to be built has ben considered as a critical information infrastructure that has been has also involved cyber security experts across different spectrums with an oversight also from the Ministry of National Security. Government has a future plan of building a robust machine learning capabilities into the system to help aid climate change forecasting, disease spread, addressing issues with food security, etc.

 

The government of Ghana decides to form an extensive stakeholder team of experts involving consultants from all concerned sectors indicated. The government of Ghana has a systems development team that you are made the Chief Systems information Officer to lead the development team.

 

As the Chief Systems Information Systems Officer and the leader of the special team tasked to ensure the feasibility, planning. execution, deployment, configuration, and maintenance of this nationwide project, solve the following:

(a) Making critical reference to elements in the case study above, explain and justify why you will prefer four (4) out of eight (8) of the below listed models to aid your team in developing different parts or all aspects of the required system for the government of Ghana. [5 marks each]

1. Waterfall model

2. Rapid Application Development model

3. Component-based development

4. The formal methods model

5. The unified process or Rational Unified Process (RUP)

6. Agile model

7. Spiral model

8. Prototype model

 

NB: Support your justification with relevant literature with articles indexed in high reputable places Scopus. Use journal articles such as Journals in IEEE Xplore, ACM digital library, Association for Information Systems (AIS) eLibrary, IET library, Engineering Index of Elsevier, BCS computer Journals etc. At least 70% of the justifications should come from scientific publications. You can also use other resources such as ITU databases, EU documentations on e-agriculture, UN FAO etc

 

(b) Effectively applying the methods of capturing and specifying user and system requirements helps in designing good systems that meets goals of the e- agricultural information system, discus four (4) out of the below approaches for eliciting, collecting, and developing requirements and support your discussions with best practices and lessons learned from other implemented works and published documents (Journal, white papers etc.) In your discussion, provide further justifications using suitable software process model(s) for your selected approaches. Relate your discussions and justifications to the elements of the case study given above [5 marks each]

1. Group interviews and one-to-one interviews/ meetings

2. Requirements gathering tools eg Axia’s RFI/RFP

3. Brainstorming and workshops

4. Feasibility study and current system documentation

5. Use case modelling e.g. UML

6. Observation and Questionnaires

7. Prototyping

8. JRD (Joint Requirements Development)

 

 

NB: Support your justification with relevant literature with articles indexed in high reputable places Scopus. Use journal articles such as Journals in IEEE Xplore, ACM digital library, Association for Information Systems (AIS) eLibrary, IET library, Engineering Index of Elsevier, BCS computer Journals etc. At least 70% of the justifications should come from scientific publications. You can also use other resources such as ITU databases, EU documentations on e-agriculture, UN FAO etc

 

Question 2 (20 marks)

 

As newer and better approaches continue to emerge, information systems are forced to adopt and incorporate these newer approaches in order to continuously provide cutting edge solutions to businesses. Business models and organisational behaviours do affect the rapid adaptation and evolution of information systems as well as the tools and techniques engaged in developing such information systems.

 

A good case is the effect of COVID-19 on businesses today. Restaurants were heavily affected by partial and full lockdowns. Educational institutions were heavily affected and health institutions were overwhelmed at the early stages. Certain countries at a point have to encourage cashless approaches of doing business whist supply chains were disrupted across the globe. Zoom application and other meeting platform have increased in patronage and have also undergone rapid security adaptability changes to meet certain demands of users.

 

Most business and institutions that stood the shocks waves of the effect of the virus were the businesses that were built to stand or adapt easily to rapid changes. Adaptation to rapid changes in business processes are essential and we are expecting rapid changes in business environments, and these have influenced and affected how information systems are built.

 

The Agricultural system to be built by the Government of Ghana must have capabilities that makes it support disparate devices and multilingual software systems since integration must occur for different vendor-based systems and across different geographical areas. Another critical feature of the system is its ability to evolve and accommodate future changes and new technologies rapidly. This ability makes the system agile.

 

Agility, scalability, interoperability and rapid adaptability are some of the critical needs of systems that rapidly evolve over time. Business processes evolve over time and adaptive project management approaches to systems development have become an integral part of system development teams. Adaptable systems tend to give more competitive advantage to businesses. These systems require rigorous work from system development and business process modelling teams. Present day information processing systems are built to accommodate dynamic modelling techniques in order to make them easily adaptable to business models and respond to changing business requirements. The development of these information systems will require the engagement of dynamic system development methodologies, tools and techniques.

 

(a) Discuss and analyse how

i. Dynamic System Development methods,

ii. Extreme Programming approaches

are providing some solutions to the development of adaptable business information systems in an ever-evolving business environment with rapid changes to business processes and technology disruptions.

[5 marks for each]

 

 

(b) Discuss and analyse how the following information systems project management approaches can help project teams in effectively capturing and specifying user and system requirements in such a way that system failures can be avoided.

iii. Adaptive information systems project management

iv. Extreme information systems project management

[5 marks for each]

 

 

NB: Support your justification with relevant literature with articles indexed in high reputable places such as Scopus. Use journal articles such as Journals in IEEE Xplore, ACM digital library, Association for Information Systems (AIS) eLibrary, IET library, Engineering Index of Elsevier, BCS computer Journals etc. At least 70% of the justifications should come from scientific publications.

 

Criteria for Assessment
Reflection, critical analysis and discussion (50% weighting)	Knowledge and understanding (30% weighting)	Evidence of reading (10% weighting)	Referencing & bibliography (5% weighting)	Presentation, grammar and spelling (5% weighting)