Reference no: EM133776977
Introduction
Case Study: Elevating Student Advising with AI Chatbot System
Dakota State University is a large institution with diverse academic programs and a substantial student population. As a way to improve student support services, the university administration has decided to implement a chatbot for advising. This chatbot aims to provide students with quick and efficient assistance regarding course selection, academic planning, registration procedures, and other related queries. With the business process analyzed, it is time to determine the ideal acquisition strategy and physical architecture.
Objectives
Understand system acquisition strategies and their application in system design contexts
Develop proficiency in creating an alternative matrix to compare and evaluate different options or alternatives
Articulate nonfunctional requirements
Design system architectures that align with nonfunctional requirements
Develop comprehensive hardware and software specification forms
Instructions
The student is expected to complete the tasks below. Completion of the tasks will yield a document with a variety of inputs. The inputs will form your final output as your assignment. Any sources used must be cited. Please utilize the formatting guidelines provided with this template.
Task Description
The following information should be used to complete the assignment:
System Acquisition Information:
Budget Allocation: Dakota State University has earmarked $100,000 for the acquisition of a chatbot system, with provision for additional funds to cover maintenance and future upgrades.
User Requirements: The chatbot must provide 24/7 accessibility to accommodate students' varying time zones and schedules. It should also offer multilingual support to serve the diverse student population. Integration with the university's Student Information System (SIS) is imperative for real-time access to academic records and course offerings. Additionally, the chatbot should deliver user-friendly interactions and personalized recommendations based on individual academic histories and preferences, all while prioritizing the security of sensitive student data.
Scalability: Anticipating a gradual increase in usage over time, the university requires a chatbot system that can seamlessly scale to meet growing demands without compromising performance.
Vendor Evaluation: In selecting a vendor, the university will assess proposals from established providers with a track record in developing AI-powered chatbots for educational institutions. Evaluation criteria include vendor reputation, customer feedback, and evidence of customized solutions aligned with the university's unique needs.
Architecture Design Information:
System Integration: The chatbot system must integrate seamlessly with existing university infrastructure, encompassing the SIS, website, and mobile applications. APIs will likely be necessary to facilitate smooth data exchange between disparate systems.
Artificial Intelligence: Core to the chatbot's intelligence will be Natural Language Processing (NLP) and Machine Learning (ML) algorithms. By leveraging supervised learning models trained on historical advising data, the chatbot can continually enhance response accuracy and relevance. Furthermore, mechanisms for continuous learning will ensure adaptation to evolving student requirements and preferences.
Hosting and Deployment: Cloud-based hosting solutions offer the flexibility and scalability required for seamless deployment and management of the chatbot system. Priority must be given to data privacy and compliance with pertinent regulations such as GDPR or CCPA.
Determine Acquisition Strategy:
Reference Figure 6-5 to discern the most suitable system acquisition strategy for the implementation of the university chatbot.
Create Alternative Matrix:
Utilize Figure 6-6 as a guide to construct an alternative matrix that substantiates the chosen system acquisition strategy.
Determine Nonfunctional Requirements:
Referencing Figures 7-5 through 7-8, delineate the nonfunctional requirements pertinent to the chatbot system. Employ Figure 7-12 as a framework to organize and articulate these requirements effectively.
Design the System Architecture:
Employing Figure 7-9 as an illustrative example, devise a system architecture mapping that correlates the identified nonfunctional requirements with prevalent architecture designs. Ensure coherence and alignment between the architecture and the specified requirements.
Develop Hardware and Software Specification Form:
Utilize Figure 7-10 as a model to craft a comprehensive hardware and software specification form tailored to the specifications of the university chatbot. Take into account the factors delineated in Figure 7-11 to inform the selection of hardware and software components conducive to the chatbot's functionality and performance requirements.
3.2
Utilize a CASE tool to develop a user interface that facilitates interlinking between interface screens, facilitating seamless navigation. It's imperative to submit a fully-fledged user interface design inclusive of navigational elements.
Design Specifications:
Interface:
Adopt a sleek and minimalist design featuring a chat window for user interaction.
Implement a personalized welcome message: "Welcome to DSU Advising Chatbot! How may I assist you today, [Name]?"
Menu:
Provide an intuitive menu comprising the following options:
Course Selection
Degree Requirements
Registration Assistance
General Inquiries
Outputs:
Course Selection:
Present a listing of available courses, tailored to the user's major and current semester.
Include essential details such as course name, description, prerequisites, and availability.
Incorporate filtering functionality to facilitate course selection based on elective requirements.
Degree Requirements:
Display the user's degree program requirements, highlighting completed courses and outstanding obligations.
Offer strategic insights for future course selection to expedite degree completion.
Registration Assistance:
Provide a user-friendly, step-by-step guide through the registration process.
Offer practical advice for crafting a well-balanced class schedule to optimize the user's academic experience.
Objectives
Identify and analyze the diverse needs and preferences of potential users of an emergent system
Apply principles of user-centered design to create an intuitive and navigable interface
Understand and apply industry-standard UI elements, metaphors, and icons to ensure consistency and usability
Demonstrate the ability to integrate various interface components, such as menus and outputs, into a cohesive prototype
Apply critical thinking and problem-solving skills to iteratively improve the user interface based on evaluation results and feedback
Instructions
The student is expected to complete the tasks below. Completion of the tasks will yield a document with a variety of inputs. The inputs will form your final output as your assignment. Any sources used must be cited. Please utilize the formatting guidelines provided with this template. Submission instructions are available below at the completion of your assignment.
Task Description
Understanding the Users:
Utilize ChatGPT to generate personas for 5 student users. Create a table detailing user profiles and their anticipated interactions with the chatbot (Refer to Figure 8-8).
Organizing the Interface:
Develop a site map to outline the primary components of the chatbot interface (Refer to Figure 8-11).
Defining Standards:
Formulate a table delineating UI standards, metaphors, objects, actions, and icons (Refer to Figure 8-25).
Construct a template for the user interface adhering to the established standards (Refer to Figure 8-27).
Developing a Prototype:
Produce an electronic mockup or simulation of the user interface incorporating the provided design information. The resulting creation will be your prototype (Refer to Figure 8-29).
Ensure inclusion of the interface, menu, and output components, drawing inspiration from the introduction (Refer to Figures 8-16 and 8-22).
Interface Evaluation and Testing:
Conduct a walk-through evaluation of the developed user interface, enlisting the feedback of a peer or acquaintance.
Submit the initial user interface along with a table summarizing the feedback received from the evaluator (Place the feedback table above the user interface).
Objectives
Create a physical data flow diagram (DFD) from logical and sequential DFD steps
Create a structure chart that aligns with best practices in program design
Evaluate and categorize the different types of data used in systems
Create a physical entity relationship diagram from decomposing a DFD
Justify the decision-making process behind the selection of a normalized or denormalized ERD
Calculate volumetrics for your system
Instructions
The student is expected to complete the tasks below. Completion of the tasks will yield a document with a variety of inputs. The inputs will form your final output as your assignment. Any sources used must be cited. Please utilize the formatting guidelines provided with this template. Submission instructions are available below at the completion of your assignment.
Task Description
All modeling MUST be completed using a CASE tool of your choice.
Complete this intellectual exercise that involves the program design and data mapping centered around a key function of an academic advising chatbot. You have the options of course selection, academic planning, or registration procedures to explore.
Develop an AI-generated prompt that identifies the logical steps within the DFD for one of the three advising functionalities listed above.
Following the logical flow you've outlined, craft a detailed physical DFD, akin to what's exemplified in Figure 9-4 of our text.
Progress to devising a structure chart that encapsulates the primary functionality of your DFD represents. Inform your structure chart by using the guidelines set forth in Figure 9-13 and aligned with principles found in Figures 9-14 through 9-17.
Tabulate the data types utilized within the chatbot's system for your selected function, drawing parallels to the illustration provided in Figure 10-6.
Create a generative AI prompt that will aid in discerning the logical components for an entity-relationship diagram (ERD) based on the functionality selected for your DFD.
Transform this into a tangible ERD, consulting Figure 10-8 for structure. In this step, we will:
Convert entities to tables or files
Transition attributes to fields
Assign primary keys
Assign foreign keys
Incorporate system-related elements
Create a generative AI prompt designed to suggest methods of denormalizing your ERD. Look to Figure 10-14 as a reference point as you begin to formulate the denormalized ERD.
Construct an additional denormalized physical ERD based on your insight from the previous step.
To conclude your CASE modeling, present a brief rationale for choosing one of the ERDs to be utilized in the ongoing project.
Complete your assignment by determining the chatbot's volumetrics, arranging your findings in a table reminiscent of Figure 10-18. Utilize the example scenario provided below as a benchmark for your calculations.
Example Scenario:
An academic advising chatbot at DSU will assist 10,000 students. The chatbot handles details related to students, courses, and enrollments. Each student typically enrolls in on average 4 courses each semester. The university offers 500 courses.
Estimated Record Sizes:
Student:
Student ID: 10 bytes
Name: 50 bytes
Email: 30 bytes
Major: 20 bytes
Year: 10 bytes
Total = 120 bytes
Course:
Course ID: 10 bytes
Name: 30 bytes
Description: 100 bytes
Credits: 10 bytes
Department: 20 bytes
Total = 170 bytes
Enrollment:
Student ID (reference): 10 bytes
Course ID (reference): 10 bytes
Semester and year: 10 bytes
Total = 30 bytes