Computer gameplay and social media are the two most common forms of entertainment in the digital age. Many scholars share the assumption that leisure-time digital consumption is associated with CS affinity, but there is a dearth of research evidence for this relationship. Female students generally spend less time on gaming and more time on social…

Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…

Educational software data promises unique insights into students' study behaviors and drivers of success. While much work has been dedicated to performance prediction in massive open online courses, it is unclear if the same methods can be applied to blended courses and a deeper understanding of student strategies is often missing. We use pattern…

Online tools provide unique access to research students' study habits and problem-solving behavior. In MOOCs [Massive Open Online Courses], this online data can be used to inform instructors and to provide automatic guidance to students. However, these techniques may not apply in blended courses with face to face and online components. We report…

We develop a random forest classifier that helps assign academic credit for a student's class forum participation. The classification target are the four classes created by student rank quartiles. Course content experts provided ground truth by ranking a limited number of post pairs. We expand this labeled set via data augmentation. We compute the…

Most of the emphasis on mining online assessment logs has been to identify content-specific errors. However, the pattern of general "consistency" is domain independent, strongly related to performance, and can itself be a target of educational data mining. We demonstrate that simple consistency indicators are related to student outcomes,…

Research directed toward a better understanding of the computer user/computer machine relationship has increased in recent years. To identify what factors may predict success in computer programming, 286 college students from three computer classes (160 from introductory programming; 60 from Cobol programming; and 66 from senior level programming)…

Through interviews and classroom observations, this study investigated the academic help-seeking and interactions of high school girls with their computer science classmates in both a private school and a public school setting. The study explored five aspects of this help-seeking interaction: (1) females as a gender minority in computer science;…

The predictors of students' completed and planned enrollments in college level computer courses were examined. A total of 195 college freshman and sophomore students (102 females and 93 males) who were enrolled at a large land-grant university in the southern region of the midwestern United States completed instruments measuring computer…

This study was an examination of the usefulness of a statistical regression approach to identify prospective Engineering and Information and Computer Science (ICS) applicants most likely to succeed at the University of California at Irvine (UCI). The specific purpose was to determine the extent to which preadmissions measures such as high school…

The attitudes of educators toward computers were assessed as well as their attitude change while taking an introductory microcomputer course. Sex and age differences were also investigated. Subjects included a sample who were surveyed by mail and a group of 22 teachers who were enrolled in a microcomputer course. A 44-item attitude questionnaire…

This study was conducted to examine the extent to which one's demographic characteristics, previous experience, aptitudes, and attitudes may be indicative of probable success in learning about computers. Information was derived from two National Science Foundation (NSF)-funded programs designed to retrain experienced teachers to become K-12…

This study examined the effects of increased computing experience on the computer anxiety of 101 first year preservice teacher education students at a regional university in Australia. Three instruments measuring computer anxiety and attitudes--the Computer Anxiety Rating Scale (CARS), Attitudes Towards Computers Scale (ATCS), and Computer…

This study examined the effect of two computer literacy courses (one was offered online, and the other was offered through traditional methods) at the Middle East Technical University (Turkey). The two courses were compared in terms of their effectiveness on computer attitudes of student-teachers. The study also explored the other factors that…