Philosophy of Computer Science: An Introductory Course

There are many branches of philosophy called “the philosophy of X,” where X = disciplines ranging from history to physics. The philosophy of artificial intelligence has a long history, and there are many courses and texts with that title. Surprisingly, the philosophy of computer science is not nearly as well-developed. This article proposes topics that might constitute the philosophy of computer science and describes a course covering those topics, along with suggested readings and assignments

Lessons Learned from Development of a Software Tool to Support Academic Advising

We detail some lessons learned while designing and testing a decision-theoretic advising support tool for undergraduates at a large state university. Between 2009 and 2011 we conducted two surveys of over 500 students in multiple majors and colleges. These surveys asked students detailed questions about their preferences concerning course selection, advising, and career paths. We present data from this study which may be helpful for faculty and staff who advise undergraduate students. We find that advising support software tools can augment the student-advisor relationship, particularly in terms of course planning, but cannot and should not replace in-person advising.Comment: 5 Figures, revised version including more figures and cross-referencin

QuizMap: Open social student modeling and adaptive navigation support with TreeMaps

In this paper, we present a novel approach to integrate social adaptive navigation support for self-assessment questions with an open student model using QuizMap, a TreeMap-based interface. By exposing student model in contrast to student peers and the whole class, QuizMap attempts to provide social guidance and increase student performance. The paper explains the nature of the QuizMap approach and its implementation in the context of self-assessment questions for Java programming. It also presents the design of a semester-long classroom study that we ran to evaluate QuizMap and reports the evaluation results. © 2011 Springer-Verlag Berlin Heidelberg

Synergistic Team Composition

Effective teams are crucial for organisations, especially in environments that require teams to be constantly created and dismantled, such as software development, scientific experiments, crowd-sourcing, or the classroom. Key factors influencing team performance are competences and personality of team members. Hence, we present a computational model to compose proficient and congenial teams based on individuals' personalities and their competences to perform tasks of different nature. With this purpose, we extend Wilde's post-Jungian method for team composition, which solely employs individuals' personalities. The aim of this study is to create a model to partition agents into teams that are balanced in competences, personality and gender. Finally, we present some preliminary empirical results that we obtained when analysing student performance. Results show the benefits of a more informed team composition that exploits individuals' competences besides information about their personalities

Entrepreneurship in American Higher Education

Presents recommendations by the Kauffman Panel on Entrepreneurship Curriculum in Higher Education on making entrepreneurship a key element in the curriculum, co-curriculum activities, and university management. Includes profiles of innovative programs

Determining the Degree to Which Ideational Behavior Predicts Occupational Identity Achievement in Emerging Adult College Students Preceding Entry into the Fourth Industrial Revolution Workforce

As emerging adults transition into the Fourth Industrial Revolution (4IR) workforce, it is essential to understand the factors that predict successful occupational identity achievement, as automation will impact human occupational identity crises. This descriptive cross-sectional study implemented a correlation design to determine the degree to which ideational behavior predicts occupational identity achievement preceding entry into the 4IR workforce. Using a sample of 166 emerging adult college students from a Mid-Atlantic, diverse, four-year university, data were collected using Runco’s Ideational Behavior Scale (RIBS) and Melgosa’s Occupational Identity Achievement subscale (OIA). Results showed that ideational behavior significantly predicted occupational identity achievement (p \u3c .016), as it was uncovered that emerging adults’ degree of ideational behavior explains 3.5% of the variance of their occupational identity achievement (R2 \u3c .035), as higher levels of ideational behavior are related to higher levels of occupational identity achievement. The results also concluded that emerging adults’ demographics showed no significance after a multiple linear regression analysis (p \u3c .246), but total ideational behavior scores remained significant (p \u3c .015). These findings suggest that ideational behavior is a strong predictor of emerging adults’ occupational identity achievement proceeding entry into the 4IR workforc

Education Challenges and Coping Mechanisms for Artificial Intelligence in Primary and Secondary Schools

The application of artificial intelligence (AI) education at the primary and secondary levels has far-reaching implications for the universalization of AI education, the cultivation of AI talent for national growth, and the improvement of student intellectual competency. This article focuses on the history of AI education in China and the challenges it faces in terms of course standards, teaching materials, personnel availability, and instructional strategies. Suggestions for coping tactics include adjusting course standards; creating a scientific textbook structure; expanding the availability of high-quality AI instructors; and promoting fundamental AI education through multi-agency collaboration. It is hoped that this study will help improve how AI is taught in elementary and secondary schools