Introductory Computer Science Course Research Articles

Rethinking Undergraduate Computer Science Education: Using the 4Es Heuristic to Center Students in an Introductory Computer Science Course

Rethinking Undergraduate Computer Science Education: Using the 4Es Heuristic to Center Students in an Introductory Computer Science Course

Reproducing Predictive Learning Analytics in CS1

Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first student pass–fail prediction approach proposed by Van Petegem and colleagues (2022) in a different CS1 course. Using student submission and self-report data, we investigated the reproducibility of the original approach, the effect of adding self-reports to the model, and the interpretability of the model features. The results showed that the original approach for student dropout prediction could be successfully reproduced in a different course context and that adding self-report data to the prediction model improved accuracy for the first four weeks. We also identified relevant features associated with dropout in the CS1 course, such as timely submission of tasks and iterative problem solving. When analyzing student behaviour, submission data and self-report data were found to complement each other. The results highlight the importance of transparency and generalizability in learning analytics and the need for future research to identify other factors beyond self-reported aptitude measures and student behaviour that can enhance dropout prediction.

Student-Centered Computing: Teacher Experiences in a New Introductory Computer Science Curriculum

Objectives. The goal of this paper is to introduce and describe a new introductory computer science course. Research results from the implementation of this curriculum will be presented to demonstrate the nature of teachers’ experiences with the curriculum. Participants. Participants are teachers implementing the new curriculum at two schools in the metro Atlanta area. Study Method. This paper is partly descriptive, presenting the theory underlying the newly developed curriculum as well as its various features. An organizing framework, the Teacher Accessibility, Equity, and Content (TEC) rubric from Weintrop et al. (2019) [ 1 ], is used to structure the curriculum description. Teacher perceptions were gathered via both structured interviews and short online enactment surveys. These perceptions are summarized and presented thematically, corresponding to the features of the curriculum. Findings. A newly developed introductory computer science (CS) curriculum, Student-Centered Computing (SCC), utilizes project-based learning (PBL) and culturally authentic practices (CAPs) to help promote a sense of belonging and intent to persist within computer science among all students. Teachers successfully implemented the curriculum and generally found it to be beneficial for their students, though they struggled with some of the pedagogical demands of project-based learning as well as some of the most advanced technical content associated with the music coding and app development platforms. Conclusions. This paper provides a detailed overview of a year-long introductory computer science curriculum focused on the creation of culturally relevant digital artifacts. The curriculum represents a strong effort to make CS content relevant and appealing to the full range of students by relating it to their lives and experiences. Teacher surveys and interviews revealed that both teachers and students had positive views of the course. However, teaching using inclusive PBL pedagogy and culturally authentic practices takes skill and practice by teachers, supporting the need for CS teachers to have good pedagogical training as well as a strong knowledge of computer science to create a classroom environment that promotes success for all students.

Implementation of blended learning approach in teaching introductory computer science course

Information communication and technology has great impact on modern education architecture of 21st century. This research intends to analyze the effectiveness of blended learning considering its basic principles and factors. Also, this study is focused on determining core problems of blended learning thus highlighting its design approach. A descriptive and inferential statistical analysis has been conducted on the data that reveal that the majority of students prefer blended learning system regardless their major, gender and any other factors if they have good infrastructure and effective electronic platform. It is recommended that for effective implementation of blended system there should be opportunities of face to face as well as online synchronous, and non-synchronous communication between students and teachers.

Engineering Students’ Experiences of Assessment in Introductory Computer Science Courses

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Contribution:</i> This study evaluates the generalizability of previously identified perceptions among engineering students of assessments in introductory programming (CS1). The students’ perceptions of their instructors’ and teaching assistants’ (TAs) roles in these assessments are also studied, and differences based on prior programming experience, gender, and course explored. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Background:</i> Basic programming skills are desirable also for students who are not majoring in computer science (CS). Students’ experience of assessments has not been fully explored. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Research Questions:</i> 1) How do engineering students experience the assessment (lab assignments, midterm exam, and project) in their CS1 courses? 2) What are the students’ perceptions of the TAs and instructors in relation to these assessment situations? 3) What significant differences can be found based on students’ prior experience in programming, gender, and course? <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Methodology:</i> Previously identified themes from an interview study worked as a framework for the formulation of 25 statements used in a survey among 137 students in six CS1 courses (second part of a mixed-method study). Descriptive statistics, Mann–Whitney U Test, and Kruskal–Wallis tests with Bonferroni corrections, were used to analyze the data. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Findings:</i> Laboratory assignments were experienced as an opportunity to learn while the exams were viewed as predictable. The projects were perceived as authentic, although varying in difficulty, and as a huge leap from the lab assignments. Students perceived the instructors to put their touch on the course but viewed their TAs as carrying out the assessments, and experienced variations between TAs. Female students experienced these variations to a larger extent and perceived received feedback as less useful.

Implementation of blended learning approach in teaching introductory computer science course

Information communication and technology has great impact on modern education architecture of 21st century. This research intends to analyze the effectiveness of blended learning considering its basic principles and factors. Also, this study is focused on determining core problems of blended learning thus highlighting its design approach. A descriptive and inferential statistical analysis has been conducted on the data that reveal that the majority of students prefer blended learning system regardless their major, gender and any other factors if they have good infrastructure and effective electronic platform. It is recommended that for effective implementation of blended system there should be opportunities of face to face as well as online synchronous, and non-synchronous communication between students and teachers.

Interactions between self‐regulated learning and assessment for learning in an undergraduate introductory computer science course

AbstractMany introductory computer science (CS) courses are intended to address the increased demand for computer literacy and the development of cross‐cutting concepts and practices of computational thinking (CT). Colleges and universities offer introductory CS courses every semester toward this end. The issue is centered on how to support CT learning in a large introductory CS course. To do it, an introductory CS course was designed to enrich CT by embedding short episodes of assessments to facilitate learning (AfL) and to support students’ self‐regulated learning (SRL). This chapter begins by articulating the intricacies of the underlying processes of SRL, principles of AfL, and computational thinking practices in CS. Using the undergraduate introductory CS course referred to above, key practices of SRL and AfL will be illustrated to demonstrate how student learning of CS programming is structured with various online and offline supports. The chapter then concludes by appraising aspects of this CS course with practical suggestions for supporting student SRL and their learning of CS programming.

Increasing Women's Participation in CS at Large Public Universities: Issues and Insights

Despite rapidly growing interest in Computer Science (CS), CS has the second lowest participation rate for women of all science and engineering degrees, according to a recent report by the US National Science Board [16]. The reasons for women's underrepresentation and their experiences may differ from university to university. Universities are very different in terms of types of students, student profiles, students' socio-economic status, race, number of students, admission requirements, and resources. For example, some universities can create gender balance in introductory courses through selective admission. However, typically, admission practices in large public universities are not able to achieve gender balance for CS majors. As a result, there are lower percentages of women in the CS major in large public universities than in selective schools. In addition, large public universities tend to have a larger number of CS students when compared to private universities. To understand women students' experiences and struggles in computer science at a large public university in the United States and to find ways to intervene in favor of gender equity in computer science, we conducted in-depth interviews with women students in introductory programming courses. In this article, we present women students' experiences, struggles, expectations and offer potential interventions based on the findings to encourage women to consider CS as their major and stay in the CS major. Our interview data shows there is a persistent effect of lack of prior programming experience and gender bias that leads to a negative experience for women students in introductory CS courses. This article presents the challenges faced by women in CS and provides their recommendations for attracting and retaining women students in CS at large public universities.

A Gender-Based Comparison of the Effects of Face-to-Face and Online Learning on Student Performance in Introductory Computer Science Courses

Introductory computer science courses help students, regardless of their majors, keep up with the rapid pace of change in the workplace. However, such courses are commonly perceived as being difficult. Although many studies have discussed the importance of online introductory computer science courses, there is a dearth of studies investigating the effectiveness of this delivery mode when the same assessment tools are used as in the traditional delivery mode. Moreover, it is unclear how students of different genders perform in both online and traditional face-to-face introductory computer science course sections when they receive the same instructional content. The purpose of this study is to expand the existing literature by examining the academic achievement of students in an introductory computer science course through the evaluation of grades obtained from online and traditional face-to-face course sections. Additionally, the study aims to explore any gender-based variations between the two delivery modes. The sample size included 589 first-year students in an introductory computer science course at a public university in Saudi Arabia. The participants were selected randomly from different sections. The results confirm the findings of previous studies suggesting that there are no gender-based differences in students’ performance in introductory computer science. Additionally, this study makes a valuable contribution to the existing body of literature by demonstrating that students who receive introductory computer science instruction through online delivery mode achieve significantly higher performance than students who receive the same instruction through traditional face-to-dace delivery mode. Moreover, this study found that both female and male students who receive introductory computer science instruction through online delivery mode perform significantly better than male students who receive instruction through traditional face-to-face delivery mode, indicating that online learning may be a more effective mode of delivery for students of both genders.

Modularization for mastery learning in CS1: a 4-year action research study.

Computer programming is a skill of increasing importance in scientific and technological fields. However, in introductory computer science (CS1) courses in higher education, approximately one in every three students fails. A common reason is that students are overwhelmed by an accelerated and inflexible pace of learning that jeopardizes success. Accordingly, in the computer science education literature it has been suggested that the pedagogical philosophy of 'mastery learning,' which supports students progressing at their own pace, can improve academic outcomes of CS1 courses. Nevertheless, few extended mastery learning implementations in CS1 have been documented in the literature, and there is a lack of guidance and best practices to foster its adoption. In this paper, we present a four-year action research study in which a modular mastery-based CS1 course was designed, evaluated and improved in successive iterations with cohorts of engineering freshmen in a Latin American research university (N = 959). In the first year of the intervention, only 19.3% of students passed the course in their first semester attempting it. In successive iterations, the instructional design, teaching and learning activities, course content, and course management were iteratively improved such that by the fourth year of offering 77.1% of students passed the course in their first semester. Over this period, course attrition was reduced from 25.0% to 3.8% of the cohort, and students' mean time spent in the course decreased from 23.2weeks (SD = 7.38) to 14.9 (SD = 3.64). Results indicate that modularization for mastery learning is a viable approach for improving academic results in a CS1 course. Practical considerations towards successful implementation of this approach are presented and discussed.

Reducing Workload in Short Answer Grading Using Machine Learning

AbstractMachine learning methods can be used to reduce the manual workload in exam grading, making it possible for teachers to spend more time on other tasks. However, when it comes to grading exams, fully eliminating manual work is not yet possible even with very accurate automated grading, as any grading mistakes could have significant consequences for the students. Here, the evaluation of an automated grading approach is therefore extended from measuring workload in relation to the accuracy of automated grading, to also measuring the overall workload required to correctly grade a full exam, with and without the support of machine learning. The evaluation was performed during an introductory computer science course with over 400 students. The exam consisted of 64 questions with relatively short answers and a two-step approach for automated grading was applied. First, a subset of answers to the exam questions was manually graded and next used as training data for machine learning models classifying the remaining answers. A number of different strategies for how to select which answers to include in the training data were evaluated. The time spent on different grading actions was measured along with the reduction of effort using clustering of answers and automated scoring. Compared to fully manual grading, the overall reduction of workload was substantial—between 64% and 74%—even with a complete manual review of all classifier output to ensure a fair grading.

The influences of computer gameplay and social media use on computer science identity and computer science career interests

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 computer science (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 media than do male students, so a gender comparison perspective is helpful. Using multinomial logistic regression analysis on a national sample of 10,197 U.S. college students in introductory CS courses, we found that frequent computer gameplay was strongly associated with an increase in the probability of CS career interest relative to a Non-STEM career interest (β = -0.17, se = 0.06, p < .01) for both male (N = 7214) and female students (N = 2659). In contrast, increased social media use predicted a higher CS career interest relative to a Science/Engineering career interest (β = 0.12, se = 0.06, p < .05) for female students by 8%, however, a lower interest for male students by 4%.

Students’ expert-like attitudes in calculus and introductory computer science courses with active-learning pedagogy

ABSTRACT Background and Context Computer Science has traditionally had poor student retention, especially among women. Prior work has found that student attitudes are a key factor to retention, especially with “weedout” courses such as Calculus. Objective To determine how student attitudes towards CS 1 and Calculus change over active-learning courses with explicit real-world connections, and the implications for at-risk groups in CS, including women and students without prior experience in CS. Methods We use two validated instruments, the Computer Attitudes Survey (CAS) and the Mathematics Attitudes and Perceptions Survey (MAPS), both of which derive from the Colorado Learning Attitudes about Science Survey (CLASS), to compare student attitudes in Calculus I and CS 1. Our analysis includes 109 students for the CAS and 73 for the MAPS. Findings CS 1 students began the course with CAS scores higher than observed in prior work, and post-course CAS scores were even higher overall. Calculus students started the course with MAPS scores in line with prior work, but unlike prior work we find that overall MAPS scores did not decline during the semester. Women’s reported interest in math increased significantly during the semester. Students with prior computer science experience began CS 1 with higher overall CAS scores, while students with prior calculus experience began Calculus with similar overall MAPS scores but much higher reported interest. Implications Difference in student attitudes between the courses may show why Calculus acts a “weedout” course for Computer Science. This highlights the importance of instructors demonstrating the usefulness of Calculus.

Building a gender-inclusive secondary computer science program: teacher led and stakeholder supported

ABSTRACT Background Despite ongoing calls for prioritizing K-12 computer science (CS) education, an enduring gender gap exists. Objective We explored one high school CS program where female participation was consistently higher than state averages to better understand how the program was developed. Method Using a case study method, data were collected over three-months through interviews, observations, course documents, student reflections, and researcher reflections. Constant comparative analysis was employed to analyze data throughout and following data generation. Findings Recruitment and teacher support were key practices. Recruitment practices included letter writing campaigns and recruiting from introductory CS courses. Teacher support came from counselors, administrators, and other teachers. While the CS program was consistently more gender-inclusive, the focus when building the program had been on supporting all students, not only female students. Implications Recruitment should be active and purposeful, but using academic indicators for targeted recruitment campaigns can limit student exposure. Teachers need support for broadening participation, particularly from counselors and administrators, who must also be aware of what CS is and their role in these efforts. Opportunities for coteaching within CS programs can be beneficial for growth. Overall, broadening participation must be a holistic effort, supported by school-wide stakeholders, not only CS teachers.

Preparing First-Year Engineering Students to Think About Code: A Guided Inquiry Approach

In the wake of the so-called fourth industrial revolution, computer programming has become a foundational competency across engineering disciplines. Yet engineering students often resist the notion that computer programming is a skill relevant to their future profession. Here are presented two activities aimed at supporting the early development of engineering students’ attitudes and abilities regarding programming in a first-year engineering course. Both activities offer students insights into the way programs are constructed, which have been identified as a source of confusion that may negatively affect acceptance. In the first activity, a structured, language-independent way to approach programming problems through guided questions was introduced, which has previously been used successfully in introductory computer science courses. The team hypothesized that guiding students through a structured reflection on how they construct programs for their class assignments might help reveal an understandable structure to them. Results showed that students in the intervention group scored nearly a full letter grade higher on the unit’s final programming assessment than those in the control condition. The second activity aimed to help students recognize how their experience with MATLAB might help them interpret code in other programming languages. In the intervention group, students were asked to review and provide comments for code written in a variety of programming languages. A qualitative analysis of their reflections examined what skills students reported they used and, specifically, how prior MATLAB experience may have aided their ability to read and comment on the unfamiliar code. Overall, the ability to understand and recognize syntactic constructs was an essential skill in making sense of code written in unfamiliar programming languages. Syntactic constructs, lexical elements, and patterns were all recognized as essential landmarks used by students interpreting code they did not write, especially in new languages. Developing an understanding of the static structure and dynamic flow required of programs was also an essential skill which helped the students. Together, the results from the first activity and the insights gained from the second activity suggest that guided questions to build skills in reading code may help mitigate confusion about program construction, thereby better preparing engineering students for computing-intensive careers.

Student Agency in a High School Computer Science Course

This study explores student agency in the context of a culturally authentic computer science (CS) curriculum implemented in an introductory CS course in two high schools. Drawing on focus group and interview data, the study utilizes qualitative research methods to examine how students exercise critical agency as they engage in the course and how the curriculum supports student agency. Findings suggest three ways in which the curriculum served as a context for student agency: (1) gaining CS knowledge and skills that students then apply to address real-world needs and problems, (2) creating opportunities to “try-on” or improvise new identities and/or envision “future selves” in CS, and (3) engaging in personally relevant project work that leverages assets students brought to their experience with the curriculum. Implications for CS education research and practice are discussed.

Shifting Beliefs in Computer Science: Change in CS Student Mindsets

Two studies investigated change in computer science (CS) students’ implicit intelligence beliefs. Across both studies, we found that the strength of incremental and entity beliefs changed across time. In Study 1, we found that incremental beliefs decreased and entity beliefs increased across the semester. Change in implicit intelligence beliefs was similar for students taking introductory and upper-division courses. In Study 2, growth curve analysis revealed a small linear change in incremental beliefs across time but no change in entity beliefs—these trends were similar for students enrolled in introductory and upper-division CS courses. Across both studies, change in implicit intelligence beliefs was not associated with academic achievement in CS. Findings provide preliminary evidence that shifts in implicit intelligence beliefs occur as students progress through the CS curriculum. Finally, findings support that mindset interventions may be more effective if delivered at the beginning of the semester before shifts in beliefs occur.

Training Teaching Assistants in Assessment of Lab Assignments in Computer Science at a Swedish University

Teaching assistants (TAs), students who assist the faculty, are widely used in computer science (CS) courses. Previous studies have, however, shown that TAs could be poorly prepared and need training. Particularly, an interview study has shown that one of the areas where the TAs experience uncertainty is when assessing students’ oral presentations of their lab assignments. Based on that result and by interviewing course coordinators, we have developed and offered training workshops about assessment in CS. We invited our TAs in the introductory CS courses to participate on a voluntary basis. By distributing pre-workshop surveys at the beginning of each semester, and post-workshop surveys at the end of the semesters, to both workshop attendees (50) and non-attendees (44), we studied how the TAs conducted the assessments and what impact the training workshop had on their self-reported practice. Both surveys had 11 identical statements that the TAs were asked to rate on a 7-point Likert scale. We also conducted interviews with four workshop attendees and three non-attendees. The results showed a significant difference between the two groups in the post-workshop survey: workshop attendees disagreed more with the statement “I try to assess students' understanding rather than the program”, which is more in line with the instructions given. In addition, when comparing pre- and post-workshop answers, the workshop attendees stated that they were less inclined to ask for help, experienced that the lab instructions were not detailed enough, and were more inclined to ask questions that convinced them that the students had written the program themselves. In the control group, no significant differences between pre- and post-tests were found.

Examining women’s differential pathways into computer science by BA and BS degree programs

ABSTRACT Background and Context Women are severely underrepresented in computer science (CS). Understanding varied entry points into CS may promote women’s participation in the field. Objective This study identifies experiences that influenced women’s matriculation into CS majors, and pathways into CS based on participants’ enrollment in bachelor of arts (BA) or bachelor of science (BS) degree programs. Method Semi-structured interviews were conducted with 13 women completing CS bachelor’s degrees at a public institution in the U.S. Findings Findings show different entry points into CS based on whether women matriculated into the site institution’s College of Engineering (pursued a BS degree) or College of Arts and Sciences (BA degree). For most, introductory CS courses were critical to choosing a CS major. BS students entered college with existing STEM interests and received early exposure to CS via curricular requirements. BA students entered CS courses and majors comparatively later, often based on social encouragement. Implications Degree program structures and curricula influence students’ exposure to CS and their major choices. Since most BA participants did not consider a CS major until their second year, flexible curricula can provide critical access for students with limited computing experience.

Students’ Engagement with Podcast during Lockdown – An Analysis of Interaction Footprints in a Computer Science Course

This paper addresses a remote teaching activity that consists, for students, in being exposed to podcasts instead of classic face-to-face theoretical lessons. In particular, the paper discusses potential impact of podcasts on students’ engagement in an introductory Computer Science course.