Data Analysis Research Assistant

The project necessitates proficiency in computer programming and skills for qualitative data analysis, interpretation, and visualizing findings. A background in coding is essential, as is the ability to categorize qualitative data for applying statistical methods, particularly with non-numeric attributes. Proficiency in engaging with qualitative data to extract meaningful insights, identify trends, and discover correlations is a critical requirement. The project's culmination will be a paper underpinned by supporting visualizations and statistical evidence.

Level UP- MacEwan: Data sets creation - Phase 6

We would like students to help us with creating content that is aligned with our vision, mission, and sector. We will ensure the student has a clear understanding of what these elements are for our organization. The project is a project that is developing a web-based application to generate synthetic datasets for students. The application is to create datasets either based on tools actual data provided by the user, or the user can create their own customized data sets. The application creates a unique dataset for each studentinstructor, allows the isntructor to create queries, and then marks the students' submissions. The project is composed of three phases. Phase 1: Creation of synthetic datasets. Phase 2: Develop a customization process for creating the datasets. Phase 3: Developing a dataset test bank. Phase 4: Creating a query builder for the instructor. Phase 5: Develop a process to mark the student's answers to the query. We will provide guidance to all students.

Level UP- MacEwan: Data sets creation - Winter 2024

We would like students to help us with creating content that is aligned with our vision, mission, and sector. We will ensure the student has a clear understanding of what these elements are for our organization. The project is a project that is developing a web-based application to generate synthetic datasets for students. The application is to create datasets either based on tools actual data provided by the user, or the user can create their own customized data sets. The application creates a unique dataset for each studentinstructor, allows the isntructor to create queries, and then marks the students' submissions. The project is composed of three phases. Phase 1: Creation of synthetic datasets. Phase 2: Develop a customization process for creating the datasets. Phase 3: Developing a dataset test bank. Phase 4: Creating a query builder for the instructor. Phase 5: Develop a process to mark the student's answers to the query. We will provide guidance to all students.

SoB - Teaching Assistant for Principles of Accounting course- Winter 2024

The main goal of this project is to assist faculty members who are teaching Principles of Accounting at MacEwan University in creating examples, developing model answers to questions and supporting the study of other students. This includes connecting with faculty members to get guidance and then helping other students in understanding some topics.