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Machine Learning Education for Artists, Musicians, and Other Creative Practitioners

This article aims to lay a foundation for the research and practice of machine learning education for creative practitioners. It begins by arguing... (more)

Integrating Ethics within Machine Learning Courses

This article establishes and addresses opportunities for ethics integration into Machine-learning (ML) courses. Following a survey of the history of... (more)

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... (more)

Social Genesis in Computing Education

It is common to think of learning as the acquisition of knowledge by an individual learner. Starting a century ago, Lev Vygotsky developed a different perspective on learning, initiating a tradition of educational research whose momentum and influence continue to grow. One of Vygotsky's key principles is the general genetic law of cultural... (more)

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... (more)

Pedagogy that Supports Computer Science for All

The Computer Science (CS) for All movement has taken hold of the United States and CS education is rapidly expanding across nations throughout the... (more)

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 article, we outline design... (more)

A New Look at Novice Programmer Errors

The types of programming errors that novice programmers make and struggle to resolve have long been of interest to researchers. Various past studies have analyzed the frequency of compiler diagnostic messages. This information, however, does not have a direct correlation to the types of errors students make, due to the inaccuracy and imprecision of... (more)

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... (more)

NEWS

Call for Papers: Special Issue on Re-Entering Computing through Emerging Technology

This special issue focuses on the intersection of emerging technology and computing education, presenting empirical and theory-based research that aims to expand the current knowledge base on women’s experiences, their strategies as they navigate computing career pathways, and their challenges in working in computing fields.

For detailed information, please read the call for papers. Deadline for extended abstracts is March 15th, 2020.

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.

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.

Please note that ACM TOCE's review process is double-blind, and papers that are not properly anonymized will be returned to authors, thus delaying the review process

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

Female performance and participation in computer science - a national picture

The change in the English computing curriculum and the shift towards computer science (CS) has been closely observed by other countries. Female participation remains a concern in most jurisdictions, but female attainment in CS is relatively unstudied. Using the English national pupil database, we analysed all exam results (n=5370064) for students taking secondary school exams in 2016 focusing on those students taking GCSE computer science (n=60736) contrasting this against ICT (n=67359). Combining gender with ethnicity and poverty indicators, we find that poorer females are significantly more likely to take computing than richer females. CS is popular amongst ethnic minority females with white girls showing the worst proportional representation of all the female ethnic groups. ICT was far more equitable for females and poorer students than CS. CS females typically get better grades than their male peers. However, when controlling for average attainment in other subjects, males get 0.31 of a grade higher. Female relative underperformance in CS is most acute amongst large female cohorts and girls studying in mixed gender schools. Girls do significantly better than boys in English when compared to CS, supporting theories around female strengths lying outside STEM subjects. The move to introduce CS into the English curriculum and the removal of ICT look to be having a negative impact on female participation and attainment. Using the theory of self-efficacy we argue that the shift towards CS might decrease the number of girls choosing further computing qualifications or persuing computing as a career. Computing curriculum designers and teachers need to carefully consider the inclusive nature of their computing courses.

Teaching Abstraction in an Introduction to Computer Science Course for 7th Graders

Abstraction is one of the most fundamental ideas in computer science (CS), and as such, according to Bruner, it should be taught spirally, starting as early as possible and revisited at every level of education. However, teaching this concept to novices is a very complicated task, as has been emphasized by many CS and mathematics education experts. A framework for teaching abstraction to novice students in the context of algorithmic problem solving was introduced by Armoni [4]. We studied the effect of this framework in an introductory CS course for 7th-graders, in which Scratch was used as the programming language for implementing algorithmic solutions. Our findings indicate that the framework was effective for developing CS abstraction skills as well as other related skills and aspects, such as the volume and quality of script documentation, the use of initialization processes, and the perception of the nature of CS. It also significantly improved students general CS knowledge as well as their programming skills.

Developing a Computing Identity Framework Understanding Computer Science and Information Technology Career Choice

This paper expands on knowledge of computing identity by building on what is known about prior identity models in science and mathematics education. The model theorizes three primary sub-constructs that contribute to the development of a computing identity: belief in one's performance/competence, interest, and recognition in computing. Drawing on data from a nationally representative survey of more than 1,700 college students at 22 colleges and universities, the study tested the alignment of the theorized model to the measures on the survey. Confirmatory Factor Analysis was used to validate whether the appropriate measures loaded on the three separate sub-constructs. Predictive validity was also established by testing whether the computing identity measures predicted the choice of a computer science career. The results reveal that a computing identity proxy based on the theorized measures was a highly significant predictor of students' computer science and information technology career choice (p<0.0001). In addition, this work also established criterion-related validity by showing gender differences that had been found by prior work in computing. Finally, the theorized measures were found to be reliable and internally consistent. The educational understanding of computing identities may provide an important tool to help researchers and practitioners improve student persistence in computer science.

Plagiarism in Programming Assessments: A Systematic Review

This paper is a systematic review of work in the computing education literature on plagiarism. The goal of the review is to summarize the main results found in the literature and highlight areas that need further work. Despite the the large body of work on plagiarism, no systematic reviews have been published so far. The reviewed papers were categorized and analyzed using a theoretical framework from the field of Fraud Deterrence named the "Fraud Triangle". According to this framework, fraudulent behavior occurs when the person is under "pressure", perceives the availability of an "opportunity" to commit fraud and "rationalizes" the fraudulent behavior in a way that makes it seem not unethical to him or her. The review found the largest amount of the reviewed papers to discuss ways for reducing the "opportunity" to plagiarize, as well as tools for detecting plagiarism. However, there is a clear lack of empirical work evaluating the deterrent efficacy of these strategies and tools. The reviewed papers also included mentions of a wide range rationalizations used by computing students when justifying plagiarism, the most important of which are rationalizations that stem from confusion about what constitutes plagiarism. Finally, work on the relationship between "pressure" in computing courses and plagiarism was found to be very scarce and incommensurate with the significant contribution of this factor to plagiarism.

The Teacher Accessibility, Equity, and Content (TEC) Rubric for Evaluating Computing Curricula

In response to the growing call to bring the powerful ideas of computer science to all learners, education decision makers, including teachers and administrators, are tasked with making consequential decisions on what curricula to use. Often, these decision makers have not been trained in computer science and are unfamiliar with the concepts taught and tools used. This is especially true in K-12 contexts where computer science expertise is less prevalent. To aid in the decision-making process around computing curricula, this paper introduces the TEC Rubric. The TEC Rubric is comprised of three main categories: Teacher Accessibility, Equity, and Content designed to support educational decision makers and designers when it comes to computing instruction. Along with presenting the full rubric and the process used in its creation, this paper describes two examples of the rubric in action. First, the TEC Rubric is used to evaluate two widespread computer science curricula to demonstrate its evaluative capacity highlighting differences between the two curricula. Second, we show how the TEC Rubric can be used to help inform the design of new K-12 computing curricula. Overall, the TEC Rubric is designed to serve as a useful resource in the ongoing quest to bring effective, equitable, and engaging computing instruction into schools around the world.

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