Leveraging Technology for Just-In-Time Content Remotely Accessible
General description of the project
Just in Time Learning: Initiated through a recent grant award from the Minority Serving Engineering Improvement Program (MSEIP) focuses on the college experience of students studying computer science, mathematics, and data science with the goal being bringing a just in time focus to their academics. Technology skills may be boosted via a synchronous or asynchronous self-learning environment or portal bringing communities together and offering “just in time training” (Wilkie, 2013; Shift, 2021). A review of LinkedIn Learning, Facebook Groups, Instagram Groups, Youtube videos, and other social media provides extensive examples of “just in time” learning/training already available to the masses. In this scenario curricular content is more controlled for individuals who are interested in boosting their knowledge and understanding through small chunk offerings of information available to students through their university website. In this manner the user feels they need a bit more training in a self-paced fashion. This satisfies the need for increased access. Now the university degree is not the singular method to learn coding, aspects of AI, robotics, etc. Rather, incremental learning and not having to wait for an expert has become a most compelling intervention empowering the worker or the individual in need of greater expertise at a moment’s notice (Shift, 2021; Brame, 2013; Pappas, 2016).
Technologies
Examples of the VR learning models developed (and some still in development) are offered for context across the various expert disciplines of the faculty involved in this project.
Professor Ling Xu’s (computer science mobile app development with VR integration) research involves 3D modeling, VR game development, android app development, and procedural arts. In these projects, students have learned the fundamentals of Human-Computer Interaction and software development, at the same time gained hands-on expertise in interface design, prototyping, and implementation with coding for various platforms.
Professor Ting Zhang’s (computer science with web-based and robotic applications) research involves the study of robotics, neuroimaging, and artificial intelligence (AI). Specifically, the cutting-edge techniques in computer science, electrical engineering, and biomedical engineering are investigated to advance interdisciplinary research approaches.
Professor Katarina Jegdic’s (mathematics and machine learning applications) JIT research’s main goal of this research project was to utilize VR (Virtual Reality) headsets to visualize multidimensional data sets in data science. An important step in machine learning modeling and in data science, in general, is Exploratory Data Analysis (EDA) that includes data visualization using a variety of graphs and charts. However, these visualization techniques are often complex due to data consisting of a large number of input variables. There are several machine learning models that enable us to reduce the number of input variables, including the Principal Component Analysis (PCA). PCA is based on the Singular Value Decomposition of matrices and the main idea is to project data points onto only the first few principal components to obtain lower dimensional data while preserving as much of the data’s variation as possible.
Professor Katherine Shoemaker’s (datascience with use of large databases) JIT research targets learning tools commonly used in data science analytics. The challenge was utilizing virtual reality technology to visualize the data science tools, their applications, and the deliverables.
Explain project results
This project is in year three, but has exposed almost 20 undergraduate research students to the Virtual Reality technology over the last four semesters. All UGs have access to the products generated by the VR technology at the UHD Scholars Academy website: https://www.uhd.edu/academics/sciences/scholars/booting-stem-just-in-time/index.aspx
Why it should be considered best practice?
This project is innovative related to technology and student success. Only time will tell if it is considered a best practice. But it is definitely an innovative practice to accessibility.
Highlights of your proposed presentation
Figure 1. Scenes developed in Unity using VR headset to be used in gaming application.
Figure 2. Examples of tutorial movie sessions using VR and Oculus headset.
Figure 3. Perceptron, logistic regression, and artificial neural networks.
Figure 4. RStudio programming and data visualization
The Evaluation Committee will evaluate submitted proposals based on the following criteria. Each area will be rated on a scale from 1 to 5 (1= non-satisfactory; 5 =outstanding), for a maximum of 45 points.