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Leveraging Targeted Regions Of Interest By Analyzing Code Comprehension With Ai-Enabled Eye-Tracking, Md Shakil Hossain
Leveraging Targeted Regions Of Interest By Analyzing Code Comprehension With Ai-Enabled Eye-Tracking, Md Shakil Hossain
Electronic Theses and Dissertations
Code comprehension studies techniques for extracting information that give insights on how code is understood. For educators teaching programming courses, this is an important but often difficult task, especially given the challenges of large class sizes, limited time, and grading resources. By analyzing where a student looks during a code comprehension task, instructors can gain insights into what information the student deems important and assess whether they are looking in the right areas of the code. The proportion of time spent viewing a part of the code is also a useful indicator of the student's decision-making process. The goal of …
Developing And Validating A Machine Learning-Based Student Attentiveness Tracking System, Andrew L. Sanders
Developing And Validating A Machine Learning-Based Student Attentiveness Tracking System, Andrew L. Sanders
Electronic Theses and Dissertations
Academic instructors and institutions desire the ability to accurately and autonomously measure the attentiveness of students in the classroom. Generally, college departments use unreliable direct communication from students (i.e. emails, phone calls), distracting and Hawthorne effect-inducing observational sit-ins, and end-of-semester surveys to collect feedback regarding their courses. Each of these methods of collecting feedback is useful but does not provide automatic feedback regarding the pace and direction of lectures. Young et al. discuss that attention levels during passive classroom lectures generally drop after about ten to thirty minutes and can be restored to normal levels with regular breaks, novel activities, …
Using Ai-Enabled Gaze Tracking System To Understand Comprehension Patterns Of Computer Science Students, Bradley Boswell
Using Ai-Enabled Gaze Tracking System To Understand Comprehension Patterns Of Computer Science Students, Bradley Boswell
Electronic Theses and Dissertations
Academic institutions and instructors lack the ability to accurately assess the moment-to-moment attentiveness of students in classrooms where students’ faces are obscured by computer monitors. This can cause the lectures of Computer Science, Information Technology, or other lab-based courses to be incorrectly-paced, which can lead to students having an overall poorer grasp of the subject material. We propose a system for real-time accurate detection of classroom attentiveness using monitor-mounted webcams and eye trackers, along with a Convolutional Neural Network machine learning model (NiCATS). Through the use of a neural network, we produce an initial attentiveness score based on student webcam …