non-CS Majors Research Articles

Increasing Diversity in Lifelong AI Education: Workshop Report

AI is rapidly emerging as a tool that can be used by everyone, increasing its impact on our lives, society, and the economy. There is a need to develop educational programs and curricula that can increase capacity and diversity in AI as well as awareness of the implications of using AI-driven technologies. This paper reports on a workshop whose goals include developing guidelines for ensuring that we expand the diversity of people engaged in AI while expanding the capacity for AI curricula with a scope of content that will reflect the competencies and needs of the workforce. The scope for AI education included K-Gray and considered AI knowledge and competencies as well as AI literacy (including responsible use and ethical issues). Participants discussed recommendations for metrics measuring capacity and diversity as well as strategies for increasing capacity and diversity at different level of education: K-12, undergraduate and graduate Computer Science (CS) majors and non-CS majors, the workforce, and the public.

Promoting Computational Thinking Skills in Non-Computer-Science Students: Gamifying Computational Notebooks to Increase Student Engagement

Computational thinking (CT) skills are becoming increasingly relevant for future professionals across all domains, beyond computer science (CS). As such, an increasing number of bachelor's and master's programs outside of the CS discipline integrate CT courses within their study program. At the same time, tools such as notebooks and interactive apps designed to support the teaching of programming concepts are becoming ever more popular. However, in non-CS majors, CT might not be perceived as essential, and students might lack the motivation to engage with such tools in order to acquire solid CT skills. This article presents a field study conducted with 115 students during a full semester on a novel computational notebook environment. It evaluates computational notebooks and CT skills in an introductory course on information technology for first-year undergraduates in business and economics. A multidimensional evaluation approach makes use of pre- and post-test surveys, lectures, and self-directed laboratory sessions tracking analytics. Our findings suggest that, in the process of learning CT for non-CS students, engagement in active learning activities can be a stronger determinant of learning outcomes than initial knowledge. Furthermore, gamifying computational notebooks can serve as a strong driver of active learning engagement, even more so than initial motivational factors.

A Qualitative Study of Experienced Course Coordinators’ Perspectives on Assessment in Introductory Programming Courses for Non-CS Majors

Assessment plays an important role in education and can both guide and motivate learning. Assessment can, however, be carried out with different aims: providing the students with feedback that supports the learning (formative assessment) and judging to which degree the students have fulfilled the intended learning outcomes (summative assessment). In this study, we explore the instructors’ perspective on assessment within the context of introductory programming courses offered to non-computer-science majors at a public tuition-free state-funded university in a Nordic country. These courses are given to a large number of students and also employ several teaching assistants (TAs). We used constructivism as a basis for our study and investigated how instructors implement formative and summative assessments, how they view their role, and what expectations they have of their TAs in these assessments. We interviewed seven course coordinators (main instructors for introductory programming courses with additional administrative duties but without formal responsibility of the grading) and analyzed 205 course artifacts, such as syllabi, lab assignment instructions, and course material from the cross-department TA training course. The results showed that course coordinators use formative and summative assessments both separately and within the same activity. They view themselves as responsible for the assessments, as the planners and material developers, as the organizers and administrators, and as monitors of the assessments. However, the results also showed that these course coordinators delegate much of the responsibility for the assessments to their TAs and expect TAs to both grade the students and provide them with feedback and guidance. In addition, the TAs are also expected to act as informants about their students’ performance. The course coordinators’ role entails many different aspects, where communicating through instructions to both students and TAs is essential. We see that this implementation of assessment, with lots of responsibility distributed to the TAs, could be difficult to manage for a single faculty member who is not necessarily responsible for the grading. Based on the results, we outline some recommendations, such as offering TA training.

A comparison of perceptions of CS majors and non-cs majors regarding email security

This paper describes a study designed to measure and compare the perceptions of computer science (CS) majors with those of other majors concerning the relative safety of various forms of communicat...

A comparison of CS majors and non-CS majors attitudes regarding computer security threats

This paper describes the results of a study designed to compare attitudes and experience levels regarding various aspects of computer security among college students. In particular, the study compa...

Computing with CORGIS

To successfully bring introductory computing to non-CS majors, one needs to create a curriculum that will appeal to students from diverse disciplines. Several educational theories emphasize the need for introductory contexts that align with students' long-term goals and are perceived as useful. Data Science, using algorithms to manipulate real-world data and interpreting the results, has emerged as a field with cross-disciplinary value, and has strong potential as an appealing context for introductory computing courses. However, it is not easy to find, clean, and integrate datasets that will satisfy a broad variety of learners. The CORGIS project (https://think.cs.vt.edu/corgis) enables instructors to easily incorporate data science into their classroom. Specifically, it provides over 40 datasets in areas including history, politics, medicine, and education. Additionally, the CORGIS infrastructure supports the integration of new datasets with simple libraries for Java, Python, and Racket, thus empowering introductory students to write programs that manipulate real data. Finally, the CORGIS web-based tools allow learners to visualize and explore datasets without programming, enabling data science lessons on day one. We have incorporated CORGIS assignments into an introductory course for non-majors to study their impact on learners' motivation, with positive initial results. These results indicate that external adopters are likely to find the CORGIS tools and materials useful in their own pedagogical pursuits.

Designing and deploying programming courses: Strategies, tools, difficulties and pedagogy

Designing and deploying programming courses is undoubtedly a challenging task. In this paper, an attempt to analyze important aspects of a sequence of two courses on imperative-procedural and object-oriented programming in a non-CS majors Department is made. This analysis is based on a questionnaire filled in by fifty students in a voluntary basis. The issues of the programming courses that are investigated refer to: the strategy selected for the introduction to programming; the sequence of the programming techniques and languages taught and the transition from the one to the other; students' difficulties with programming in general and with imperative-procedural and object-oriented programming in specific; the teaching and learning design of both courses; and the material that students rely on for learning programming. Based on the analysis of students' replies on the questionnaire, related work and the instructor's experience on teaching the courses, conclusions are drawn regarding all the aforementioned aspects of designing and deploying programming courses. The main contribution of the paper is the fact that all the important and interrelated aspects of a sequence of two programming courses are investigated in conjunction, providing realistic implications and guidelines for improving the quality and effectiveness of existing programming courses and designing and deploying new courses. The main results refer to the usage of a pseudo-language for an introduction to programming, the transition from procedural to object-oriented programming, the intrinsic difficulties of learning programming, and practices for a more successful teaching and learning design of programming courses.

Profiles of Motivated Self-Regulation in College Computer Science Courses: Differences in Major versus Required Non-Major Courses

The goal of the present study was to utilize a profiling approach to understand differences in motivation and strategic self-regulation among post-secondary STEM students in major versus required non-major computer science courses. Participants were 233 students from required introductory computer science courses (194 men; 35 women; 4 unknown) at a large Midwestern state university. Cluster analysis identified five profiles: (1) a strategic profile of a highly motivated by-any-means good strategy user; (2) a knowledge-building profile of an intrinsically motivated autonomous, mastery-oriented student; (3) a surface learning profile of a utility motivated minimally engaged student; (4) an apathetic profile of an amotivational disengaged student; and (5) a learned helpless profile of a motivated but unable to effectively self-regulate student. Among CS majors and students in courses in their major field, the strategic and knowledge-building profiles were the most prevalent. Among non-CS majors and students in required non-major courses, the learned helpless, surface learning, and apathetic profiles were the most prevalent. Students in the strategic and knowledge-building profiles had significantly higher retention of computational thinking knowledge than students in other profiles. Students in the apathetic and surface learning profiles saw little instrumentality of the course for their future academic and career objectives. Findings show that students in STEM fields taking required computer science courses exhibit the same constellation of motivated strategic self-regulation profiles found in other post-secondary and K-12 settings.

Teach Alice programming to non-majors

This paper presents the design and implementation of an introductory computer programming course using Alice for non-CS majors. This course gives a broad overview of computer science as an academic discipline and teaches computer programming to non-CS majors in a fun way.

Foundational actions

Often Software Engineering courses approach educating undergraduates in good processes and practices by using a simulated product development environment, following all of the steps for product development in a single semester. Some also create multi-semester projects to improve the student experience. We are in the group using multi-semester projects, but our approach differs in that we have only a single semester of project work per team, focused on the core actions used in all processes from waterfalls to XP. We call this foundational actions. Using industrial tools, processes, and evaluation methods, the students develop and integrate components of a well-specified, but major product. Emphasis is placed on teamwork, communication, and ultimately, working production code created with the foundational actions. The approach has also spun off related independent study opportunities for advanced students and even non-CS majors.

Design process for a non-majors computing course

There is growing interest in computing courses for non-CS majors. We have recently built such a course that has met with positive response. We describe our design process, which includes involvement of stakeholders and identifying a context that facilitates learning. We present evaluation results on success rates (approximately 90% of the students earn an A, B, or C) and impact of the course on students over time (80% report that the class has influenced them more than a semester later).

Do Non‐Computer Science Students Need to Program?*

AbstractShould non‐CS majors learn to program? While the 1999 National Academy of Sciences report “Being Fluent with Information Technology”1 advocates teaching programming as part of the CS‐0 experience, we challenge the assumptions upon which this recommendation rests. Our extensive review of the NECC and SIGCSE conference proceedings from 1979 to 1998 clearly shows a decline in the number of articles in which programming is taught in CS‐0 courses. Furthermore, based upon learning theory literature, we argue that conceptual understanding of computing can be acquired without learning to program. Finally, we describe our criterion‐referenced, mastery‐model course that currently enrolls approximately 2000 students per semester for a computing future that is constantly changing. Interpretation of the loadings of the discriminant analysis functions provides evidence that the students are developing conceptual understanding, rather than simply acquiring discrete skills.

Teaching Image Computation in an Upper Level Elective on Robotics

This article offers a case study of how to teach image computation in an upper level elective course on robotics with a significant number of non-Computer Science majors. The MACS 415 course at the Colorado School of Mines is required for the popular interdisciplinary undergraduate minor in Robotics and AI. It is mandated to provide a broad survey of the artificial intelligence tools available to roboticists, including image computation. Teaching image computation in a robotics elective is challenging both because of the limited time that can be spent on computer vision, and because of the attributes of the students. Non-CS majors typically do not have enough programming experience to program DSP algorithms, yet the students' preferred learning style is "hands-on." In order to reconcile this dilemma, we (1) cover a broad set of topics in class, (2) have several laboratory assignments using khoros, and (3) require the students to complete a robot project involving computer vision. The article summarizes the lessons learned to date, which are expected to be applicable to any course with non-majors involving image computation.

Using Ada in non-CS majors

2. INTRODUCTION All students attending the U.S. Air Force Academy (called USAFA hereafter) are required to take an introductory course in computer science. For the past two years, Ada 95 has been the programming language taught in that course [2]. In addition, Ada has been the “language of choice” in the computer science curriculum for several years; in some computer science courses, Ada has been used for 6 years. It appears to be fairly common for computer science professors to consider and adopt Ada as their desired programming language [3]. We have been unable to discover in the literature, however, indications that other academic disciplines are also selecting Ada for use in their curricula.

Necessity is the mother of language features

A common problem when teaching CS1 courses to non-CS majors is students' lack of motivation. This paper describes a new approach and methodology intended to solve this problem: The new approach involves a different sequencing of topics covered in most CS1 courses, and the division of the course into four units; thus exposing students to four different problems of moderate length and degree of difficulty. The new methodology consists of presenting students with problems for which the programming features learned up to that point are inadequate to solve the task. Thus, instead of presenting topics (language features) followed by a series of problems which require the student to apply specific tools, I introduce problems which create a need for new language features. This way students feel more motivated to explore new venues and participate more effectively in the decision-making process.