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The Effects of Adding Non-Compulsory Exercises to an Online Learning Tool on Student Performance and Code Copying

This study analyzes the impact of adding a review exercises module to an online tool used in a... (more)

Digital and Physical Fabrication as Multimodal Learning: Understanding Youth Computational Thinking When Making Integrated Systems Through Bidirectionally Responsive Design

This article proposes and explores the kinds of computational thinking, creative practices, design activities, and inclusive learning opportunities... (more)

A Robust Machine Learning Technique to Predict Low-performing Students

As enrollments and class sizes in postsecondary institutions have increased, instructors have sought automated and lightweight means to identify... (more)

Does Computer Game Design and Programming Benefit Children? A Meta-Synthesis of Research

It is widely believed that there are educational benefits to making computer games, but there is no systematic review of research on this topic. This... (more)

Identifying Pathways to Computer Science: The Long-Term Impact of Short-Term Game Programming Outreach Interventions

Short-term outreach interventions are conducted to raise young students’ awareness of the computer science (CS) field. Typically, these interventions are targeted at K–12 students, attempting to encourage them to study CS in higher education. This study is based on a series of extra-curricular outreach events that introduced... (more)

A Framework for Teaching Security Design Analysis Using Case Studies and the Hybrid Flipped Classroom

With ever-greater reliance of the developed world on information and communication technologies,... (more)

Learning IS Child’s Play: Game-Based Learning in Computer Science Education

Game-based learning has received significant attention in educational pedagogy as an effective way of increasing student motivation and engagement. The majority of the work in this area has been focused on digital games or games involving technology. We focus on the use of traditional game design in improving student engagement and perception of... (more)

Transformative and Troublesome? Students' and Professional Programmers' Perspectives on Difficult Concepts in Programming

Programming skills are an increasingly desirable asset across disciplines; however, learning to... (more)

Equitable Learning Environments in K-12 Computing: Teachers’ Views on Barriers to Diversity

The current efforts to expand computer science (CS) education in K-12 schools, such as the “CS for All” initiative, highlight the need... (more)

Chutes and Ladders: Institutional Setbacks on the Computer Science Community College Transfer Pathway

Community colleges play a large role in educating students who are historically underrepresented in computer science (CS), including women, Latino men, and Black men, as well as post-traditional (older or working) students. In spite of this, there is a dearth of research on the institutional factors that influence whether or not community college... (more)

Incorporating Computing Professionals’ Know-how: Differences between Assessment by Students, Academics, and Professional Experts

It is important for both computer science academics and students to clearly comprehend the differences between academic and professional perspectives... (more)

Source-code Similarity Detection and Detection Tools Used in Academia: A Systematic Review

Teachers deal with plagiarism on a regular basis, so they try to prevent and detect plagiarism, a task that is complicated by the large size of some... (more)

NEWS

July Submission Deadline Extended

Due to travel, the editor-in-chief will not be able to review July submissions until July 8. You have one extra week to submit in time for the July reviewing deadline.  

ACM TOCE Charter Updated

ACM TOCE's charter has been updated for the first time since its inception! It significantly expands TOCE's scope while reaffirming its commitment to publishing rigorous, peer-reviewed articles that make significant contributions to computing education theory, research, and practice. READ CHARTER

ACM Reappoints Editor-in-Chief

The ACM Publications Board has appointed Dr. Chris Hundhausen, current ACM TOCE editor-in-chief, to a second three-year term, which runs from August 31, 2018 through August 30, 2021. Chris is excited to continue his collaboration with the computing education community on the important work of maintaining, growing, and improving our premier archival publication for computing education research.

Submit Special Edition Proposals

ACM TOCE seeks proposals from researchers and educators interested in guest-editing special issues on topics of interest and relevance to the computing education research community. If you have an idea for a special issue, please email the editor-in-chief.

Special Edition Issues Coming Soon

ACM TOCE will soon publish accepted manuscripts from our three special issues: "Global Software Engineering," "Capstones and Projects," and "Machine Learning Education."

ACM TOCE Review Process is Now Double-Blind 

Authors who submit papers to ACM TOCE should see the paragraphs on double-blind review in the newly-updated author guidelines for details on how to anonymize their papers for submission. Papers that are not properly anonymized will be returned to authors, thus delaying the review process. 

Authors: Submit by 8:00 am on First Day of Month for Fastest Review 

ACM TOCE's monthly peer review process begins on the first day of each month. On this day, we begin reviewing all papers received by our "soft" deadline:  8:00 a.m. U.S. Pacific Time on the first day of the month. If you want your paper to be reviewed as quickly as possible, submit it just before our monthly "soft" deadline.

About TOCE

The ACM Transactions on Computing Education (TOCE) publishes high quality, peer-reviewed research articles on the teaching and learning of computing from childhood through adulthood. By establishing clear connections between theoretical, pedagogical and technological advances and student learning and teaching, TOCE articles take a scholarly approach to computing education research, and are of potential interest to a broad audience, including instructors, researchers, instructional designers, and administrators.  READ MORE

Forthcoming Articles

Design and evaluation of an "athletic" approach to soware engineering education

The rise of "tech stacks" for modern application development has produced a quandry for software engineering educators. On the one hand, competency with a tech stack makes it possible for students to develop and deploy modern, "professional" applications in a relatively short period of time, which in turn makes it more possible than ever before for students to experience "real world" software engineering issues in the classroom. On the other hand, developing tech stack competency is a non-trival undertaking, and it is increasingly difficult for students to avoid becoming mired in low-level tech stack issues that prevent them from focusing on higher level software engineering concepts and ideas. In this research, we present a new pedagogy called Athletic Software Engineering, which is designed to enable students to efficiently acquire tech stack competency in order to improve their experience of software engineering education, and present results from four years of use across six semesters and 286 students. We gathered data regarding the pedagogy from four sources including: a custom mid-semester questionnaire; the "WOD cards" that record the results of weekly assessments; self-reported student data on the number of times they repeated a "practice WOD", as well as the standard end-of-semester institutional course evaluation survey. We used this data to investigate four research questions: (1) is Athletic Software Engineering an effective pedagogy for learning software engineering; (2) Do students comply with the basic components of Athletic Software Engineering; (3) Does Athletic Software Engineering have side effects, such as creating competition, improving confidence, managing pressure, and improving focus, and (4) How can Athletic Software Engineering be improved? Our results provide strong evidence that Athletic Software Engineering is an effective pedagogy: on average, over four years, 88\% of students preferred it to a more traditional approach to software engineering education. The results also indicate that students repeat practice WODs, that they find the in-class WOD with its all-or-nothing grading scheme to be helpful for learning, that the approach creates competitive feelings, that it increases confidence, and that it helps students feel more comfortable programming under pressure.

Integrating Ethics within Machine Learning Courses

Based on a systematic literature review, the key ethical considerations and questions students should explore when using machine learning algorithms are outlined and mapped to phases within a data science project. To test student perceptions when trying to apply these questions, we then report on the findings of a case study where students in an introduction to data science class were asked to use these questions to identify the top ethical considerations within a machine learning project. The case study found that students were able to easily understand the questions and that, collectively, the students leveraged all the proposed questions to identify the potential ethical conundrums. Thus, this paper helps to provide some structure for students to explore the possible ethical situations that can arise when using machine learning. This research contributes towards the goal of creating an environment where data science students are able to internalize an ethical thinking mindset as well as providing those students with the knowledge of the types of ethical situations that they might need to contemplate throughout the life of a machine learning project.

Programming Embodied Interactions with a Remotely Controlled Educational Robot

Contemporary research has introduced robots in the classroom, but there is a limited number of studies about the effects of alternative embodied interactions with them on learning and attitudes. Apart from the goal of the robot and how the robot will interact with its environment another important aspect that should be taken into consideration is whether and how the user will physically interact with the robot. In this work, we explored the synergy between embodied learning and educational robotics through a series of programming activities in an attempt to expand students? learning in computational thinking. Thirty-six middle school students were asked to develop interfaces for controlling a robot using diverse interaction modalities, such as touch, speech, hand and full-body gestures. We measured students? perception of computing and assessed the development of their computational thinking skills by analyzing the sophistication of the projects they created during a problem-solving task. We also examined their computational practices to gain a more comprehensive view of their understandings. We found that students who programmed combinations of low embodiment interfaces or interfaces with no embodiment produced more sophisticated projects and adopted more sophisticated computational practices compared to those who programmed full-body interfaces. These findings suggest that there might be a trade-off between the appeal and the cognitive benefit of rich embodied interaction. In further work, educational robotics research and competitions might be complemented with a hybrid approach that blends the traditional autonomous robot movement with student enactment.

What Is Hard About Teaching Machine Learning to Non-Majors? Insights From Classifying Instructors' Learning Goals

Given its societal impacts and applications to numerous fields, machine learning (ML) is an important topic to understand for many students outside of computer science and statistics. However, machine learning education research is nascent, and research on this subject for non-majors thus far has only focused on curricula and courseware. We interviewed ten instructors of ML courses for non-majors, inquiring as to what their students find both easy and difficult about machine learning. While ML has a reputation for having algorithms that are difficult to understand, in practice our participating instructors reported that it was not the algorithms that were difficult to teach, but the higher-level design decisions. We found that the learning goals that participants described as hard to teach were consistent with higher levels of the Structure of Observed Learning Outcomes (SOLO) taxonomy, such as making design decisions and comparing/contrasting models. We also found that the learning goals that were described as easy to teach, such as following the steps of particular algorithms, were consistent with the lower levels of the SOLO taxonomy. Realizing that higher-SOLO learning goals are more difficult to teach is useful for informing course design, public outreach, and the design of educational tools for teaching ML.

State Case Study of Computing Education Governance

High school computing education reform efforts have been ongoing across the United States, particularly in the past decade. Although national computer science (CS) for All initiatives are promising, states retain control over education policies. Recent computing education reform efforts in Maryland focused on providing every public high school student with access to high quality high school computing courses. Such access provides exposure to computing careers and better prepares a diverse pool of students for computing majors in college. This comprehensive embedded multi-level case study examines the computing education reform efforts from 2010 through 2016. The expansion of computing education indicates that while there was positive growth, the growth is not the same for all public high school students. Despite successes, barriers at the state, Local Education Agencies (LEA), school, and classroom levels persist and are discussed. The findings in this study are applicable to other states with similar policy structures.

Pedagogy that Supports Computer Science for All

The CS for All movement has taken hold of the US and CS education is rapidly expanding across nations throughout the world. Yet as curricula and professional development opportunities are developed, key questions remain about what ?works? for engaging youth in CS education when they do not necessarily look like the majority of computer scientists nor feel like they belong in the field. In response, this study answers the questions: What teaching practices do students?who are underrepresented in CS?believe are most effective for engaging their interest in CS learning? What pedagogical actions do CS teachers identify as most effective for engaging students? And what does this effective teaching look like in introductory CS classes enrolling majority students underrepresented in the field? Through a qualitative study following three different urban high school Exploring Computer Science classrooms over an entire school year (n = 70 students, 3 teachers; >105 hours of observation data; >50 interviews with students and teachers), key pedagogical practices that had greatest impact on youth?s interest and engagement learning CS included: 1) demystifying CS by showing its connections to everyday life; 2) addressing social issues impacting both CS and students? communities; and 3) valuing students? voices and perspectives in the CS classroom. This paper shares testimonies from students and teachers, as well as examples of these teaching practices in the classroom.

Using informed design in informal Computer Science programs to increase youths' interest, self-efficacy, and perceptions of parental support

Our work is situated in research on Computer Science (CS) learning in informal learning environments and literature on the factors that influence girls to enter CS. In this paper, we outline design choices around the creation of a summer programming camp for middle school youth. In addition, we describe a near-peer mentoring model we used that was influenced by Bandura?s self-efficacy theory. The purpose of this paper, apart from promoting transparency of program design, was to evaluate the effectiveness of our camp design in terms of increasing youths? interest, self-efficacy beliefs, and perceptions of parental support. We found significant gains for all three of these concepts. Additionally, we make connections between our design choices (e.g. videos, peer support, mentor support) and the affective gains by thematically analyzing interview data concerning the outcomes found in our camps.

Predicting Women's Persistence in Computer Science- and Technology-Related Majors from High School to College

While demand for computer science and information technology jobs grows, the proportion of women entering computer science fields (CS) has declined. A critical barrier to women entering computing is the transition from high school to college. We examined factors predicting college persistence from data collected while women were in high school. Two competing models representing survey items as constructs were compared using Confirmatory Factor Analysis (CFA): the first model used Social Cognitive Career Theory which posits factors for interest, self-efficacy, perceived social supports and other affective and social constructs, the second organized by content sub-domains such as programming, inventing new applications and game design. The CFA analysis found the domain model to be a superior fit to the survey data. Using composite variables drawn from domain factors in Multinomial Regression models, we found that involvement in programming during high school was the best predictor of persistence in (both) CS and non-CS technology related majors three years later. Involvement with other sub-domains such as game design did not predict persistence, and perceived social supports also did not correlate with persistence.

A Systematic Investigation of Replications in Computing Education Research

As the societal demands for computer science professionals increase, computer science student enrollment keeps growing rapidly around the world. Computing education research plays a vital role in addressing both educational and societal challenges that emerge from the growth of computer science. As the result, the reliability of computing education research is of great importance. Reliability of a field can hardly be substantiated without replications. This study investigated the complete publication history of three major computing education conferences in the last decade (2009 - 2018), and found only 2.42% articles were replication studies. The results demonstrated the needs for more replication studies in computing education to improve its ability to shape both policy and practices.

Social genesis in computing education

In this paper, we inquire into how a teacher and students in a classroom write code together. In doing so, we treat the classroom situation not as an interaction of individual cognitive agents, but a phenomenon that is irreducibly social. We take as a theoretical basis of analysis Vygotskys genetic law of cultural development, which states that all higher-level individual mental functioning is historically preceded by and reproduces social relations between people. Using this principle, we reveal the social relations that develop in the classroom that regulate the way in which ideas are shared and code is produced for a particular coding problem. This offers a rule-regulated and dialogical model for writing code that is significantly different from the schema-based models posited in cognitive accounts of learning to program.

Brains and Blocks: Introducing Novice Programmers to Brain-Computer Interface Application Development

Brain-Computer Interface (BCI) hardware is becoming more affordable and accessible. However, there is limited work investigating ways to design software that broadens participation with BCI technology. In this article, we present a block-based programming environment designed to assist novice programmers with creating BCI applications. We also discuss learning barriers encountered by novice programmers developing neurofeedback applications. Our findings suggest that visual programming assists novice programmers with building basic BCI applications; however, students may experience understanding and learning barriers initially.

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