Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Visual and Textual Programming Languages: A Systematic Review of the Literature

It is well documented, and has been the topic of much research, that Computer Science courses tend to have higher than average drop out rates at third level. This is a problem that needs to be addressed with urgency but also caution. The required number of Computer Science graduates is growing every year but the number of graduates is not meeting this demand and one way that this problem can be alleviated is to encourage students at an early age towards studying Computer Science courses. This paper presents a systematic literature review on the role of visual and textual programming languages when learning to program, particularly as a first programming language. The approach is systematic, in that a structured search of electronic resources has been conducted, and the results are presented and quantitatively analysed. This study will give insight into whether or not the current approaches to teaching young learners programming are viable, and examines what we can do to increase the interest and retention of these students as they progress through their education.Comment: 18 pages (including 2 bibliography pages), 3 figure

Students' perceptions of paper-based vs. computer-based testing in an introductory programming course

This paper examines the preferences of students regarding computer-based versus paper-based assessment, in an introductory computer programming course. Two groups of students were surveyed about their preference between paper-based and computer-based tests and respective rationale. All students had already been assessed: one group using two paper-based tests and the other group using two computer-based tests. Both groups expressed an overwhelming preference for computer-based tests independently of their previous pro- gramming experience. We conclude that, from the students’ point of view, computer-based tests should be the used over paper-based ones for introductory programming courses. This adds to existing literature about computer-based testing of programming skills

Using the SOLO Taxonomy to Understand Subgoal Labels Effect in CS1

is work extends previous research on subgoal labeled instructions by examining their effect across a semester-long, Java-based CS1 course. Across four quizzes, students were asked to explain in plain English the process that they would use to solve a programming problem. In this mixed methods study, we used the SOLO taxonomy to categorize student responses about problem-solving processes and compare students who learned with subgoal labels to those who did not. e use of the SOLO taxonomy classification allows us to look deeper than the mere correctness of answers to focus on the quality of the answers produced in terms of completeness of relevant concepts and explanation of relationships among concepts. Students who learned with subgoals produced higher-rated answers in terms of complexity and quality on three of four quizzes. Also, they were three times more likely to discuss issues of data type on a question about assignments and expressions than students who did not learn with subgoal labeling. is suggests that the use of subgoal labeling enabled students to gain a deeper and more complex understanding of the material presented in the course

A pilot study on the impact of teaching assistant led CS1 study sessions using Peer Instruction

James Madison University’s Computer Science program strives to be a student-centered learning environment with a focus on creating a community for undergraduate success. National data reveals computer science has the lowest student retention rate compared to other STEM majors. The National Center for Women and Information Technology (NCWIT) has compiled a list of ways to retain students in Computer Science. In particular, NCWIT calls for collaboration indicate that “a sense of belonging, or a feeling of fit, is important for supporting student interest and persistence.” One aspect of creating community is the department’s longstanding commitment to provide undergraduate teaching assistants (TAs). Traditionally, TAs provide one-on-one help in the classroom and also hold supplementary lab hours in the evenings to answer questions. As part of this honors project, we have developed a new program called “The Fourth Hour” to increase student retention. Led by TAs using Peer Instruction (PI), these weekly study sessions provide a structured review of introductory topics. The aim of this research is to discover if weekly study sessions promote an environment in which students feel an increased sense of belonging and improved course material retention. In the Fall 2019 semester, JMU offered ten sections of CS149, the introductory programming course, also known as “CS1” in the literature. Each section had approximately 30 students enrolled. Four TAs were chosen to lead one study session each week using the same lesson materials. Three attitudinal surveys were administered over the duration of the semester to collect data on student demographics, self-efficacy, and sense of belonging. Pre- and post assessment results were recorded to test student course material retention. Study session attendance was also collected to discern if there was a correlation with student demographics, self-efficacy, sense of belonging, and/or course material retention. Anomalies in the data and inconsistent attendance rates limited the statistical significance of our results. However, our qualitative analysis suggests that the study sessions had a positive impact on students. As a result, the CS department is planning to continue offering the Fourth Hour program

Toward Predicting Success and Failure in CS2: A Mixed-Method Analysis

Factors driving success and failure in CS1 are the subject of much study but less so for CS2. This paper investigates the transition from CS1 to CS2 in search of leading indicators of success in CS2. Both CS1 and CS2 at the University of North Carolina Wilmington (UNCW) are taught in Python with annual enrollments of 300 and 150 respectively. In this paper, we report on the following research questions: 1) Are CS1 grades indicators of CS2 grades? 2) Does a quantitative relationship exist between CS2 course grade and a modified version of the SCS1 concept inventory? 3) What are the most challenging aspects of CS2, and how well does CS1 prepare students for CS2 from the student's perspective? We provide a quantitative analysis of 2300 CS1 and CS2 course grades from 2013--2019. In Spring 2019, we administered a modified version of the SCS1 concept inventory to 44 students in the first week of CS2. Further, 69 students completed an exit questionnaire at the conclusion of CS2 to gain qualitative student feedback on their challenges in CS2 and on how well CS1 prepared them for CS2. We find that 56% of students' grades were lower in CS2 than CS1, 18% improved their grades, and 26% earned the same grade. Of the changes, 62% were within one grade point. We find a statistically significant correlation between the modified SCS1 score and CS2 grade points. Students identify linked lists and class/object concepts among the most challenging. Student feedback on CS2 challenges and the adequacy of their CS1 preparations identify possible avenues for improving the CS1-CS2 transition.Comment: The definitive Version of Record was published in 2020 ACM Southeast Conference (ACMSE 2020), April 2-4, 2020, Tampa, FL, USA. 8 page

Pervasive Parallel And Distributed Computing In A Liberal Arts College Curriculum

We present a model for incorporating parallel and distributed computing (PDC) throughout an undergraduate CS curriculum. Our curriculum is designed to introduce students early to parallel and distributed computing topics and to expose students to these topics repeatedly in the context of a wide variety of CS courses. The key to our approach is the development of a required intermediate-level course that serves as a introduction to computer systems and parallel computing. It serves as a requirement for every CS major and minor and is a prerequisite to upper-level courses that expand on parallel and distributed computing topics in different contexts. With the addition of this new course, we are able to easily make room in upper-level courses to add and expand parallel and distributed computing topics. The goal of our curricular design is to ensure that every graduating CS major has exposure to parallel and distributed computing, with both a breadth and depth of coverage. Our curriculum is particularly designed for the constraints of a small liberal arts college, however, much of its ideas and its design are applicable to any undergraduate CS curriculum

Lessons Learned From a PLTL-CS Program

The Peer-Led Team Learning (PLTL) approach has previously been shown to be effective in recruiting and retaining students, particularly under-represented students, in undergraduate introductory CS courses. In PLTL, small groups of students are led by an undergraduate peer and work together to solve problems related to CS. At Columbia University, the Columbia Emerging Scholars Program has used PLTL in an effort to increase enrollment in CS courses beyond the introductory level, and to increase the number of students who select Computer Science as their major, by demonstrating that CS is necessarily a collaborative activity that focuses more on problem solving and algorithmic thinking than on programming. Over the past five semesters, 68 students have completed the program, and preliminary results indicate that this program has had a positive effect on increasing participation in the major. This paper discusses our experiences of building and expanding the Columbia Emerging Scholars program, and addresses such topics as recruiting, training, scheduling, student behavior, and evaluation. We expect that this paper will provide a valuable set of lessons learned to other educators who seek to launch or grow a PLTL program at their institution as well

Developing an Open-Book Online Exam for Final Year Students

Like many others, our institution had to adapt our traditional proctored, written examinations to open-book online variants due to the COVID-19 pandemic. This paper describes the process applied to develop open-book online exams for final year (undergraduate) students studying Applied Machine Learning and Applied Artificial Intelligence and Deep Learning courses as part of a four-year BSc in Computer Science. We also present processes used to validate the examinations as well as plagiarism detection methods implemented. Findings from this study highlight positive effects of using open-book online exams, with 85% of students reporting that they either prefer online open-book examinations or have no preference between traditional and open-book exams. There were no statistically significant differences reported comparing the exam results of student cohorts who took the open-book online examination, compared to previous cohorts who sat traditional exams. These results are of value to the CSEd community for three reasons. First, it outlines a methodology for developing online open-book exams (including publishing the open-book online exam papers as samples). Second, it provides approaches for deterring plagiarism and implementing plagiarism detection for open-book exams. Finally, we present feedback from students which may be used to guide future online open-book exam development

Lessons Learned From a PLTL-CS Program

The Peer-Led Team Learning (PLTL) approach has previously been shown to be effective in recruiting and retaining students, particularly under-represented students, in undergraduate introductory CS courses. In PLTL, small groups of students are led by an undergraduate peer and work together to solve problems related to CS. At Columbia University, the Columbia Emerging Scholars Program has used PLTL in an effort to increase enrollment in CS courses beyond the introductory level, and to increase the number of students who select Computer Science as their major, by demonstrating that CS is necessarily a collaborative activity that focuses more on problem solving and algorithmic thinking than on programming. Over the past five semesters, 68 students have completed the program, and preliminary results indicate that this program has had a positive effect on increasing participation in the major. This paper discusses our experiences of building and expanding the Columbia Emerging Scholars program, and addresses such topics as recruiting, training, scheduling, student behavior, and evaluation. We expect that this paper will provide a valuable set of lessons learned to other educators who seek to launch or grow a PLTL program at their institution as well