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Running Head: LAB 2 – ITRACKER PROTOTYPE SPECIFICATION 1

Lab 2 – iTracker Prototype Specification

Aran Barzanji

Old Dominion University

CS411W

Professor J. Brunelle

March 25, 2019

Version 1

LAB 2 – ITRACKER PROTOTYPE SPECIFICATION 2

Table of Contents

1. Introduction..................................................................................................................................31.1 Purpose...................................................................................................................................41.2 Scope......................................................................................................................................71.3 Definitions, Acronyms, Abbreviations..................................................................................81.4 References............................................................................................................................111.5 Overview..............................................................................................................................12

2. General Description...................................................................................................................122.1 Prototype Architecture Description.....................................................................................122.2 Prototype Functional Description........................................................................................152.3 External Interfaces...............................................................................................................16

2.3.1 Hardware Interfaces......................................................................................................162.3.2 Software Interfaces........................................................................................................172.3.3 User Interfaces...............................................................................................................17

List of Figures

Figure 1. Current Process Flow Without iTracker...........................................................................4Figure 2. Solution Process Flow With iTracker..............................................................................5Figure 3. iTracker Prototype Major Functional Components Diagram.........................................13

List of Tables

Table 1. iTracker Competition Matrix.............................................................................................6Table 2. iTracker Features – Real World Product (RWP) vs Prototype........................................14


Lab 1 – iTracker Prototype Specification

1. Introduction

Scientific research is one of the most important components of a university. Research

programs allow universities to acquire grants, which are vital to developing academic programs.

In 2018, tick researchers in the Biology department at Old Dominion University (ODU) received

$2.5 million dollars from the National Institutes of Health to study tick systems (Saunders,

2018). Enhancing the efficiency of existing research methods at ODU could be of great benefit

to the University; however, one must first consider the major challenges which are involved in

the scientific process.

Empirical data collection is one of the most time-consuming tasks in scientific research.

This is very evident in introductory Biology classes at ODU. Typically, introductory Biology

classes at most universities, including ODU, have a very large student enrollment rate (Cash,

Letargo, Graether, & Jacobs, 2011). This means that there is a large amount of paper forms that

instructors and teaching assistants must collect and analyze in Biology labs. On one hand, this

may be very beneficial – the large class sizes can be utilized to collect data on a large scale for

funded research projects. However, manual data analysis techniques cut into the already limited

instructional time in Biology labs. By taking advantage of electronic forms and decentralized

data entry, iTracker will facilitate more efficient data analysis in real time, while providing

additional time to teach class material.

Often times a large latency exists between the moment that data is collected and entered

into a digital format, to the time that data can be analyzed. The timely support of scientific

hypotheses may be hindered without the utilization of efficient research methods. iTracker is a


tool that will help to resolve some of these issues by decentralizing the data entry, analysis, and

calculation portions. With immediate processing of raw data, iTracker will allow for expeditious

data analysis, which will foster a much greater appreciation of the scientific process.

1.1 Purpose

Figure 1. shows the current process of scientific research without iTracker. As the figure

shows, the process can greatly benefit from the use of software. The current process is simply too

tedious and can be made much more efficient.

Figure 1. Current Process Flow Without iTracker


Figure 2 shows how iTracker can help to ease some of the burdens of data collection in

the scientific research process. By allowing for efficient entry of collected data into a

decentralized system, iTracker will allow for a better scientific research process. Increased

efficiency is extremely valuable in the scientific research field, as they may lead to more

grants/funding for the school and it’s researchers.

Figure 2. Solution Process Flow With iTracker

The iTracker application will be web based, primarily due to the versatility that web

applications provide. The most important benefit is that iTracker can be run from most smart

devices, regardless of the operating system supported by the device. Students and instructors will

be authenticated to iTracker using registered and approved credentials. Once logged in, menus

will be shown on screen for students and instructors. Students will be able to input data into an

electronic form which will be made to simulate the forms that they are filling in by hand. The

application will help to facilitate student learning and to remove the burden of data collection by


streamlining the data collection stage of scientific experimentation. Once the data has been

collected, the application will allow for statistics to be calculated quickly with one button. These

statistics include the mean, median, and standard deviation of a certain set of data. Additionally,

iTracker will provide users with visualization options in the form of graphs and charts. Finally,

the application will allow instructors to provide instructional tools and materials to their students.

Table 1 shows the comparison of iTracker to similar software applications. The table

illustrates the primary advantages that iTracker has over the competition. Most importantly, the

application is science and academically oriented, and allows for decentralized data access and

data visualization.

Table 1.

iTracker Competition Matrix

Table 1.


1.2 Scope

The iTracker prototype will involve a combination of real and simulated data. The goal of

the prototype will be to implement the majority of the highest priority features. In the Student

user-role, these features are primarily related to creating data forms and calculating statistics.

The ability to view submitted data and to visualize the data in the form of charts will also be a

high priority feature for Students. In the Instructor/Sr. Researcher role, the highest priority

features include administrative tasks, including user management, and viewing submitted student

data. Lower on the priority list of features for both roles will be the educational materials

component.


1.3 Definitions, Acronyms, Abbreviations

[Super] Administrator: Special user who has all abilities that other users have, plus the ability to

add Instructor/Sr. Researcher users.

Access Times: The time period which a certain user can access a certain material

(form/educational materials).

Analysis: The detailed examination of scientific observations, which can help to lead to a

conclusion.

C#: Object-oriented programming language developed by Microsoft like Java and C++ that is

well suited for web applications such as iTracker.

Educational Materials: PowerPoint presentations, videos, and tutorials that an Instructor user can

upload, and a Student user can view inside of iTracker.

Form: Data collection form used to gather the results of scientific observations.

Graphical User Interface (GUI): Everything that users can see and interact within the iTracker

application, including login pages, data forms, and statistics results pages.

Guest: A user who is not yet registered/approved as a Student user by an Instructor user; has

fewer privileges than Student users.

HTML: Hypertext Markup Language, used to present and stylize web pages.

Instructor: A type of user that has all the privileges of a Student user, plus the ability to view and

manage Student User’s data, upload educational materials, and approve/deny Guest user

applications to become Student users.

JavaScript: An object-oriented programming language that is often used in web development to

create interactive effects on web pages.


Mean: The statistical average of a set of data calculated by summing all the data in the set and

dividing it by the number of items in the set.

Median: In a set of data that is ordered, the exact middle number of the set. If there is no exact

middle, the median is then the two middle numbers divided by 2.

MSSQL: Microsoft SQL Server, a relational database created by Microsoft that is like Oracle but

uses T-SQL instead of PL/SQL.

Observation: The process of monitoring certain entities for use in scientific research applications.

Outlier Data: Data that has been flagged by iTracker as possibly being invalid when compared to

known viable/valid data; may be caused by experimental or user error.

PHP: Hypertext preprocessor, web programming/scripting language that is particularly suited for

the development of a web application such as iTracker.

Processing: The transforming of raw data into a usable form that allows for more efficient

analysis.

Sr. Researcher: See Instructor; is part of the same user group as Instructor users and has the same

application permissions and abilities but may be a lab teaching assistant instead of a

professor.

Standard Deviation: A measure of the amount of variation that the values in a set of data have.

Student: The main type of user in the iTracker application who is part of a lab section and has an

Instructor user.

Survey Data: The data that has been collected as part of the research observation process.

Tick Questing: A behavior in ticks that involves waiting, usually on a tree branch, leaf, or blade

of grass, for a warm body to come into proximity so that it can latch onto the warm body.


Viable Data: Student data that has not been flagged by iTracker as being outlier data; is

considered valid and trustworthy.

Virtual Machine (VM): A virtual computer.

Visualization: The representation of data to allow for easier drawing of conclusions in scientific

experiments.

WebView Wrapper: An Android extension that allows web pages to be displayed inside an

Android mobile application.

Windows Server: An operating system developed by Microsoft for server applications; can

utilize MSSQL.


1.4 References

Android Developers. (n.d.). Retrieved September 21, 2018, from Android Developers Web site:

https://developer.android.com/guide/webapps/webview/

Barzanji, Aran. 2019. Lab 1 – iTracker Product Description. Old Dominion University,

CS411W, Professional Workforce Development II, Spring 2019. Retrieved March 19,

2019, from Web Site:

https://www.cs.odu.edu/~411yello/labs/lab1/abarz001_lab1v2.docx.

Cash, C. B., Letargo, J., Graether, S., & Jacobs, S. (2011). An Analysis of the Perceptions and

Resources of Large University Classes. Life Sciences Education, 10(2), 164-174.

doi:10.3897/bdj.4.e7720.figure2f

David Gauthier. (n.d.). Retrieved September 25, 2018, from ODU People Directory Web site:

https://www.odu.edu/directory/people/d/dgauthie/

Dr. Holly Gaff. (n.d.). Retrieved September 25, 2018, from Dr. Holly Gaff - Tick Research Team

Web site: https://sites.wp.odu.edu/hgaff/

Jessa, T. (2010, September 19). What are the Steps of the Scientific Method. Retrieved January

21, 2019, from Universe Today Web site: https://www.universetoday.com/74036/what-

are-the-steps-of-the-scientific-method/

Microsoft SQL Server vs. Oracle: The Same, But Different? (2016, October 26). Retrieved

September 25, 2018, from Segue Technologies Web site:

https://www.seguetech.com/microsoft-sql-server-vs-oracle-same-different/

ODU Tick Team. (n.d.). Retrieved September 25, 2018, from ODU Tick Team Web site:

https://sites.wp.odu.edu/tick-team/

https://developer.android.com/guide/webapps/webview/


Saunders, N. (2018). ODU Tick Researchers Receive $2.5 Million from the National Institutes of

Health. Retrieved October 11, 2018, from News @ ODU Web site:

https://www.odu.edu/news/2018/5/tick_research/

1.5 Overview

The rest of this document gives a general description of the iTracker prototype. This

includes the prototype architecture, prototype functional description, and a discussion of the

external interfaces (hardware, software, and user) involved in the prototype application.

2. General Description

iTracker is a web based application which will help students and instructors conduct

scientific research in a more efficient manner.

2.1 Prototype Architecture Description

The prototype software will run on an ODU Computer Science virtual machine and

utilize several web-centered languages to perform all of the necessary tasks. The virtual machine

will run WAMP (Windows, Apache, MySQL, and PHP) for the purposes of running a web

application. Windows Server 2016 will be the operating system for the virtual machine, while

Apache will serve as the web server, and MySQL will facilitate database needs. PHP will be the

primary language for programming the iTracker prototype. Since this web application will be

comprised of the main iTracker website (which hosts the iTracker documentation), HTML, CSS,

and JS will be used to stylize the front end of the web application to make the transition from the

main iTracker website to the web application feel seamless. Figure 3 shows the prototype major

functional components diagram. Real and simulated data is fed into the iTracker web application.

From there, PHP performs all of the necessary calculations and interacts with the internal


database to perform user authentication and registration tasks, while preparing a web page for

output to the user.

Figure 3. iTracker Prototype Major Functional Components Diagram


For the purposes of a prototype, the highest priority features will be able to be applied directly to

a real-world application. The two most important features are the entry of data into an electronic

form/calculation of statistics (mean, median, and standard deviation) based on the entered data.

Lower priority features will make use of simulated data, to simulate a real-world application.

Features that involve instructional materials are of the lower priority.

Table 2 shows the features that will be fully or partially implemented in the iTracker

prototype. Fully implemented features are ones that will involve real world data, while partially

implemented features will make use of simulated data. This is necessary due to certain time and

permission restrictions.

Table 2.

iTracker Features – Real World Product (RWP) vs Prototype

Table 2.


2.2 Prototype Functional Description

When a user (student or instructor) first navigates to the iTracker prototype, they will be

presented with a home page, made up of a general description of the prototype application and a

navigation bar. The navigation bar will include an About page, which will tell the user more

about the iTracker software. User management options will also be included on the navigation

bar for registering new users, and then for logging those users in.

Upon the initiation of a login request, the iTracker application will send the username and

password form data to the virtual machine’s PHP back-end. From here, PHP will interact with

the internal MySQL database to perform a user authentication operation. All student users must

be registered and approved by a higher-level user (instructor or administrator). A similar

sequence occurs when a user attempts to register a new user, however, the form data is put into a

moderation queue for later review by an instructor or administrator user.

After a user has been properly authenticated, new menu options will appear on the page.

These options will be different based on the type of user that is logged in (student,

instructor/administrators). Administrators and instructors will be able to see Calculate, Research,

Options, Students, and Awaiting Approval menu buttons, along with the previously mentioned

About button. A logout button replaces the login and register menu buttons now that the user has

been authenticated.

The Awaiting Approval page will encapsulate a list of pending registered users.

Administrators and instructors are able to approve or deny the user registration requests here.

The Students page will contain a list of the usernames of all registered students, along with their

ID number, class, and four actions for each user. These four actions are Update user, Delete user,


Grant Administrator Privileges to the user, and User Data, which will present the user’s entered

survey data.

The Options page will allow instructors, teaching assistants, and administrators to add

new items to the list of questions presented in a new form to students. It will also allow these

users to update the graph’s X axis and Y axis.

The Research page will show a list of all survey forms. This will include the name of the

survey, the date it was created, data sets inside of the survey, and options to update or delete the

survey.

The Calculate page will perform all of the mathematical calculations on the survey data

sets. These are the mean, median, and standard deviation. Also included on this page is a graph

with a X and Y axis, which will provide a visual representation of the data set observation points.

A student user will have the same abilities on all of the previously mentioned pages,

however, this user will only be presented with Calculate, Research, About, and Logout menu

options. This is done to restrict access to survey manipulation operations to teaching assistants,

instructors, and administrators.

2.3 External Interfaces

The iTracker prototype will rely on an ODU Computer Science virtual machine server.

Several hardware and software interfaces are required to make full use of iTracker.

2.3.1 Hardware Interfaces

From a user’s perspective, some type of internet connected device is required to access

iTracker. This may be a computer running Mac OS, Windows, or some type of Unix distro.

Users may also access the site using a smartphone which Android, iOS, or even Windows Phone

OS. Since iTracker is a web application, there are a large number of devices that are supported.


From the application’s perspective, a single server capable of virtualization is sufficient

for hosting the entire web application.

2.3.2 Software Interfaces

Numerous software interfaces are involved in running iTracker. Apache will be used as

the web server, MySQL will be used to create databases, and PHP will be used to do the bulk of

the calculations and data visualization. HTML, CSS, and JavaScript will also be used to generate

web pages that a user can utilize to use all of iTracker’s features. Finally, a modern web browser,

preferably Google Chrome, Mozilla Firefox, or Apple’s Safari, will be necessary to access the

iTracker application.

2.3.3 User Interfaces

Users will need an internet connected of their choice to access iTracker. As discussed

previously, there is a wide range of devices (computers, smartphones) that are supported here.

Thus, it is essentially the user’s preference which device they would like to use to connect to

iTracker.

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