Introductory CS Research Articles

Nevertheless, They Persisted: Factors that Promote Persistence for Women and Racially/Ethnically Minoritized Students in Undergraduate Computing

ABSTRACT Background and Context As computing fields aim to both expand and diversify, narrowing representation gaps in undergraduate computing majors requires focus on retaining women and racially/ethnically minoritized students to the point of degree attainment. Objective This study addresses the factors that contribute to persistence in computing majors among undergraduate students who took introductory computing courses during the first two years of college. Method Student survey data from 15 research universities in the United States were used to explore differences in persistence patterns by students’ gender and racial/ethnic identities. Further, we used logistic regression to examine factors that promote persistence in computing majors, with attention to conditional effects by gender and race/ethnicity. Findings Results show that women are less likely than men to persist in computing majors two years following completion of the introductory CS course. Findings suggest that proximal socialization experiences, specifically those related to students’ self-confidence, sense of fit, and in-class experiences, are important to student persistence in computing fields. Implications: The results suggest that peer experiences in computing are central to student persistence in the major. Hence, computing departments can act on these findings by strengthening the community within their majors and fostering positive peer interactions among students.

Gender Diversity in Computer Science at a Large Public R1 Research University: Reporting on a Self-study

With the number of jobs in computer occupations on the rise, there is a greater need for computer science (CS) graduates than ever. At the same time, most CS departments across the country are only seeing 25–30% of women students in their classes, meaning that we are failing to draw interest from a large portion of the population. In this work, we explore the gender gap in CS at Rutgers University–New Brunswick, a large public R1 research university, using three data sets that span thousands of students across six academic years. Specifically, we combine these data sets to study the gender gaps in four core CS courses and explore the correlation of several factors with retention and the impact of these factors on changes to the gender gap as students proceed through the CS courses toward completing the CS major. For example, we find that a significant percentage of women students taking the introductory CS1 course for majors do not intend to major in CS, which may be a contributing factor to a large increase in the gender gap immediately after CS1. This finding implies that part of the retention task is attracting these women students to further explore the major. Results from our study include both novel findings and findings that are consistent with known challenges for increasing gender diversity in CS. In both cases, we provide extensive quantitative data in support of the findings.

Self-evaluation Interventions: Impact on Self-efficacy and Performance in Introductory Programming

Research has repeatedly shown self-efficacy to be associated with course outcomes in CS and across other fields. CS education research has documented this and has developed CS-specific self-efficacy measurement instruments, but to date there have been only a few studies examining interventions intended to improve students’ self-efficacy in CS, and several types of self-efficacy interventions suggested by previous research remain to be tested in CS. This study attempts to address this lack of research by reporting on the results of a trial intervention intended to improve students’ self-efficacy in an introductory programming course. Students were recruited to complete a self-evaluation task, which previous research has suggested could have a beneficial impact on self-efficacy, which should in turn have a beneficial impact on course performance. Participating students’ course outcomes and self-efficacy were compared with those of the students who did not complete the self-evaluation task, using propensity score weighting adjustments to control for differences between the groups on entering characteristics and prior values of self-efficacy and course outcomes. We found that, whereas there was only marginal evidence for the self-evaluation intervention having a direct effect on self-efficacy, students who completed the self-evaluation task had significantly higher project scores during the weeks they were asked to complete it, compared to the students who did not participate. These findings suggest that there are potential benefits to incorporating self-evaluation tasks into introductory CS courses, although perhaps not by virtue of directly influencing self-efficacy.

Communicating about computational thinking: understanding affordances of portfolios for assessing high school students’ computational thinking and participation practices

ABSTRACT Background and Context: While assessment of computational thinking concepts, practices, and perspectives is at the forefront of K-12 CS education, supporting student communication about computation has received relatively little attention. Objective: To examine the usability of process-based portfolios for capturing students’ communication about their computational practices regarding the process of making electronic textile projects. Method: We examined the portfolios of 248 high school students in 15 introductory CS classrooms from largely underserved communities, using a formal rubric (top-down) to code computational communication and an open-coding scheme (bottom-up) to identify computational practices described. Findings: Students demonstrated stronger abilities to communicate about computation using text than visuals. They also reported under-assessed CT practices like debugging, iterating, and collaborating. Students of experienced e-textile teachers performed substantially better than those with novice e-textile teachers. Implications: Portfolios provide a viable addition to traditional performance or survey assessments and meet a need to promote communication skills.

Hybrid and Non-Hybrid Block-Based Programming Languages in an Introductory College Computer-Science Course

Block-based programming languages (BBLs) have been proposed as a way to prepare students for learning to program in more sophisticated, text-based languages, such as Java. Hybrid BBLs add the ability to view and edit the block commands in auto-generated, text-based code. We compared the use of a non-hybrid BBL (Scratch), a hybrid BBL (Pencil Code), and no BBL across three sections of an introductory CS course that taught Java programming, to determine whether either type of BBL offered cognitive or affective advantages for learning Java. Students in the BBL groups were surveyed about their perceptions of each BBL in terms of ease of use and helpfulness in learning Java, and all three groups were compared on their performance in Java programming. The results showed that, in this introductory CS course, neither type of BBL offered an advantage in preparing students for learning Java. These results held regardless of the students’ level of Java knowledge prior to the course.

Why do students make mistakes? an antipattern documentation about misconceptions related to CS1 introductory programming courses in Python

The purpose of this research is to identify the misconceptions held by undergraduate students when taking introductory CS1 courses using Python. The methodology of this work consisted of interviews with instructors of previous sections of an introductory CS1 course in Python at Unicamp, and through the analysis of past exams. As a result of this work, we documented a set of 28 hypothetical misconceptions in Python through the antipattern [1] format, allowing the identification of why, how, and where the mapped misconceptions usually occur. Future work involves the development of a Concept Inventory—a multiple-choice questionnaire in which each misconception is mapped to an incorrect option—in the Python programming language.

Reflections on an introductory CS course, CS15, at Brown University

Reflections on an introductory CS course, CS15, at Brown University

Helping to realize “computer science for all”: Student outcomes of self-pacing in introductory programming courses

Sparked by a series of national campaigns to increase interest in computer science, computer science departments are inundated with students who are interested in learning how to program. Despite the interest, introductory computer science course have relatively low completion rates (approximately 55% at Mason) and high rates of academic integrity violations. In response to this environment, the Computer Science department at Mason received an external grant to redesign their introductory programming courses to a self-paced, flipped format. Implementation began in Fall 2015 with a quasi-experimental methodology that tracks students from an experimental course and a control group (those who took more traditional introductory CS courses) over the course of the semester. Data collected includes grades on assignments, self-report surveys, and classroom observations. The purpose of this study is to examine the impact of a self-paced, flipped curricular design in an introductory experiential computer science course on the immediate (in course) completion. In this short lightning talk, we will present data from student surveys and classroom observations identifying any difference across the control and experimental groups. Preliminary results identify a significant increase in student completion upwards of a 20% difference across the groups. In addition to increasing knowledge of the impact of self-paced courses on student retention and success in computer science, we offer an alternative method to collect data on classroom observations via the Real-time Observation Classroom Application (ROCA). ROCA allows for efficient data collection and comparison of specific pedagogies to student engagement measures.

A refined C-based infrastructure and curriculum to support robots in introductory CS

Since 2011, a student-faculty team at Grinnell College has developed and refined a complete course package, called MyroC, comprising a C-based infrastructure, course materials, laboratory exercises, problem sets, projects, etc. for introductory computer science. Using a lab-based pedagogy, the course emphasizes imperative problem solving and utilizes the control of robots as an integrative application theme. Although this approach has had much success, on-going technical challenges have included the lack of portability, unintuitive image processing, and forced sequential processing of robot commands. This paper describes improvements to both the C library and course materials (e.g., examples, laboratory exercises, and projects) that enhance student learning through laboratory experiences. Refinements have focused upon transforming the infrastructure from an extensive, largely non-portable C++ package to a simple C environment, allowing users to work with images directly as 2D arrays of pixels, non-blocking alternatives for many robot-motion commands, and concurrent control for the movement of multiple robots. The paper also describes assessment of effectiveness, including student reactions and enrollment statistics. Finally, this paper demonstrates the effectiveness of student-faculty collaboration in course development.

A discussion on adopting peer instruction in a course focused on risk management

Peer Instruction (PI) has been shown to promote learning in introductory CS courses as well as upper-division courses such as architecture. A common thread among PI courses is that they focus on pr...

Test-first design pedagogy in introductory Java programming

Java is used in many introductory CS courses (including the AP CS course). This tutorial introduces the Java tester library that supports the test-first design pedagogy in Java from the beginning. Test-first design forces students to reason about the planned methods, to think about their behavior and the expected outcomes before designing the method bodies. Professional programmers have commented on the positive aspects of this approach: smaller methods, decreased stress, better code, higher confidence in the code correctness.

Understanding CS1 students; defective software

The Communications Web site, http://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of Communications , we'll publish selected posts or excerpts. twitter Follow us on Twitter at http://twitter.com/blogCACM http://cacm.acm.org/blogs/blog-cacm ark Guzdial writes about why teachers must grasp introductory CS students' theories about computing. Bertrand Meyer argues for the necessity of analyzing large-scale software disasters and publishing a detailed technical study.

Short mobile game development projects for introductory CS courses

Game development and mobile computing have been successfully used to increase student motivation. However, instructors with no background in mobile computing, computer graphics, and/or game develop...

Short mobile game development projects for introductory CS courses

Game development and mobile computing have been successfully used to increase student motivation. However, instructors with no background in mobile computing, computer graphics, and/or game develop...

Experimental evaluation of an educational game for improved learning in introductory computing

We are developing games to increase student learning and attitudes in introductory CS courses. Wu's Castle is a game where students program changes in loops and arrays in an interactive, visual way. The game provides immediate feedback and helps students visualize code execution in a safe environment. We compared the game to a traditional programming assignment in an introductory CS course. In our study, half of the students were randomly selected to play the learning game first and half to write a program first. Our results show that students who play our learning game first outperform those who write a program before playing the game. Students in the game-first group felt they spent less time on the assignments, and all students preferred the learning game over the program. These results suggest that games like Wu's Castle can help prepare students to create deeper, more robust understanding of computing concepts while improving their perceptions of computing homework assignments.

Breadth-first CS 1 for scientists

This paper describes an introductory CS course designed to provide future scientists with a one-semester overview of the discipline. The course takes a breadth-first approach that leverages its students' interest and experience in science, mathematics, and engineering. In contrast to many other styles of CS 1, this course does not presume that its students will study more computer science, but it does seek to prepare them should they choose to do so. In addition to describing the curriculum and resources, we summarize our preliminary assessments of this course and a comparison with the more traditional, imperative-first introduction it replaced. The data thus far suggest that this CS for Scientists course improves our students' understanding of CS, its applications, and practice.

An introduction to computer science for non-majors using principles of computation

In this paper, the design and implementation of a novel introductory computer science course for non-majors is presented. This course focuses on the major contributions in computer science from the perspective of the process of computation. This course differs from most introductory courses in computer science in that it does not include programming using a computer programming language. Students focus on algorithms and the principle of computational thinking, and use a flowchart simulator to experiment with various short algorithms and build simple computer games without dealing with programming language syntax. Steadily increasing enrollments and interest from various departments on campus indicate that this course has become a successful addition to our introductory CS offerings.

Designing, visualizing, and discussing algorithms within a CS 1 studio experience: An empirical study

Within the context of an introductory CS1 unit on algorithmic problem-solving, we are exploring the pedagogical value of a novel active learning activity—the “studio experience”—that actively engages learners with algorithm visualization technology. In a studio experience, student pairs are tasked with (a) developing a solution to an algorithm design problem, (b) constructing an accompanying visualization with a storyline, and finally (c) presenting that visualization for feedback and discussion in a session modeled after an architectural “design crit.” Is a studio experience educationally valuable? What kind of technology can best support it? To explore these questions, we conducted an empirical study of two alternative CS1 studio experiences in which students used one of two different kinds of algorithm development and visualization technology: (a) a text editor coupled with art supplies, or (b) ALVIS Live!, a computer-based algorithm development and visualization tool. We found that the students who used ALVIS Live! developed algorithms with significantly fewer semantic errors. Moreover, discussions mediated by ALVIS Live! had significantly more student audience contributions, and retained a sharper focus on the specific details of algorithm behavior, leading to the collaborative identification and repair of semantic errors. In addition, discussions mediated by both ALVIS Live! and art supplies contained substantial evidence of higher order thinking. Based on our results, we make recommendations for educators interested in exploring studio-based approaches, and we propose an agenda for future research into studio-based learning in computer science education.

A Placement Test for Computer Science: Design, Implementation, and Analysis

An introductory CS1 course presents problems for educators and students due to students' diverse background in programming knowledge and exposure. Students who enroll in CS1 also have different expectations and motivations. Prompted by the curricular guidelines for undergraduate programmes in computer science released in 2001 by the ACM/IEEE, and driven by a departmental project to reinvent the undergraduate computer science and computer engineering curricula at the University of Nebraska-Lincoln, we are currently implementing a series of changes which will improve our introductory courses. One key component of our project is an online placement examination tied to the cognitive domain that assesses student knowledge and intellectual skills. Our placement test is also integrated into a comprehensive educational research design containing a pre- and posttest framework for assessing student learning and providing valuable feedback for needed instructional revisions. In this paper, we focus on the design and implementation of our placement exam and present an analysis of the data collected to date.

Designing, implementing, and analyzing a placement test for introductory CS courses

An introductory CS1 course presents problems for educators and students due to students' diverse background in programming knowledge and exposure. Students who enroll in CS1 also have different expectations and motivations. Prompted by the curricular guidelines for undergraduate programs in computer science released in 2001 by the ACM/IEEE, and driven by a departmental project to reinvent the undergraduate computer science and computer engineering curricula at the University of Nebraska-Lincoln, we are currently implementing a series of changes which will improve our introductory courses. One key component of our project is an online placement examination tied to the cognitive domain that assesses student knowledge and intellectual skills. Our placement test is also integrated into a comprehensive educational research design containing a pre- and post-test framework for assessing student learning. In this paper, we focus on the design and implementation of our placement exam and present an analysis of the data collected to date.