Background: Ongoing debates about the structure of cognitive load theory, which traditionally distinguishes among intrinsic, extraneous, and germane cognitive load, have important implications for how cognitive load is measured in educational research. Cognitive load theorists debate the distinction between germane and intrinsic load, as well as the reliability of self-reported cognitive load measures and their ability to capture germane load. Prior critiques of cognitive load surveys may equally apply to the widely used measurement tools in computer science education.

Background: Live coding, or the process of instructors writing code in real time in front of students, is an alternative teaching method to showing students static code examples. Variations of live coding tightly coupled with more active learning approaches are common, which can make it difficult to understand the contribution of live coding alone.

Introductory programming courses can be taught in a variety of ways, including live coding, where instructors write code in real-time in front of students, or static code examples, where pre-prepared code is explained to students. While previous studies have compared live coding and static coding and their impacts on student assessment and cognitive load in large lecture environments, we present our experiences in a single lab session, highlighting student engagement differences. After presenting the same material to groups of students through a live-coding presentation and a static code presentation, we reflect on the observable differences in student engagement through an established framework of cognitive engagement. Additionally, we compare pre-surveys, post-tests, and cognitive load surveys from both groups. While our findings did not result in significant differences in student assessments, our experience highlighted differences between live and static code presentations. Live coding presentations can often take up to twice as long as static code presentations. Students may tend to ask more questions in live coding presentations, suggesting live coding provides instructors and students with more opportunities for further discussion. Live coding may also provide the instructor with additional opportunities to discuss other concepts that may not have been included in a pre-prepared presentation.

Debugging is a core skill required by programmers, yet we know little about how to effectively teach the process of debugging. The challenges of learning debugging are compounded for novices who lack experience and are still learning the tools they need to program effectively. In this work, we report a case study in which we used a think-aloud protocol to gain insight into the behaviour of three students engaged in debugging tasks. Our qualitative analysis reveals a variety of helpful practices and barriers that limit the effectiveness of debugging. We observe that comprehension, evidence-based activities, and workflow practices all contribute to novice debugging success. Lack of sustained effort, precision, and methodical processes negatively impact debugging effectiveness. We anticipate that understanding how students engage in debugging tasks will aid future work to address ineffective behaviours and promote effective debugging activities.

The ACM Special Interest Group on Computer Science Education (SIGCSE) is one of the oldest and largest SIGs, and the SIGCSE Technical Symposium is the oldest and largest of the four SIGCSE conferences. However, the vast majority of Symposium attendees and contributors are from the United States. Because SIGCSE is an international organization, this lack of geographic diversity and representation is troubling because it may stifle collaboration, membership, professional development, and dissemination of research, and have many other adverse effects.

Increasingly, languages used in computing curricula offer abstract constructs that permit list iteration by value, in addition to the traditional access by index. Given this option, this study explores the loop constructs students choose when solving a problem. We asked students from introductory programming courses to write solutions to two tasks that require iteration through array or list objects, analyzing their responses and noting coding constructs that indicate a loop-by-value strategy or a loop-by-index strategy. Consistent with previous accounts, we find that students may employ a strategy based on their experience and the required task. However, they often implement the strategy using code elements that are inconsistent with the chosen strategy, including referencing the index when a reference to the value at the location of the index is required. Some inconsistencies, such as the use of misleading variable names, do not affect program execution but often coincide with other inconsistencies that produce incorrect code. We recommend that instructors provide explicit scaffolding for the sequential introduction of iterative constructs. We note that a discussion of when each type of loop is typically used may be insufficient and suggest reinforcing habits for maintaining and checking consistency of looping strategies.

Despite decades of literature calling for research on teaching debugging, we still lack clear guidelines on how to teach debugging processes effectively. This is a significant problem as debugging is an activity that is a key component of software development and a frustrating and time-consuming barrier to students who are learning to program. In this paper we reflect on teaching and learning debugging through the lens of student beliefs about their own debugging practice. We find that few students use systematic approaches such as the scientific method of hypothesis generation and testing that is informally adopted by many software developers. Some students appeared to be satisfied with their ad hoc approaches while others expressed a desire to develop more thorough approaches.

SIGCSE is a global organization with members from well over one hundred countries, but attendance at SIGCSE conferences is not always reflective of membership as a whole. Attendance at the SIGCSE Technical Symposium is overwhelmingly from the United States, with more than 92% of all attendees in recent years having a U.S. affiliation. This panel, which includes members of the SIGCSE Board and the Symposium International Committee, will present the state of Symposium participation from outside the U.S. in an effort towards understanding what can be done to expand global participation in the Symposium. The panelists span the range from students to long-time faculty and together have computing education experience from seven countries across six continents. The panel will also solicit views from attendees on barriers to global Symposium participation and ways to improve non-U.S. participation in SIGCSE's flagship conference.

We investigate conditions in which novices make some reference errors when programming. We asked students from introductory programming courses to perform a simple code-writing task that required constructing references to objects and their attributes. By experimentally manipulating the nature of the attributes in the tasks, from identifying attributes (e.g., title or label ) to descriptive attributes (e.g., calories or texture ), the study revealed the relative frequencies with which students mistakenly omit the name of an identifying attribute while attempting to reference its value. We explain how these reference-point shifts are consistent with the use of metonymy, a form of figurative expression in human communication. Our analysis also reveals how the presentation of examples can affect the construction of the reference in the student’s solution. We discuss plausible accounts of the reference-point errors and how they may inform a model of reference construction. We suggest that reference-point errors may be the result of well-practiced habits of communication rather than misconceptions of the task or what the computer can do.

We investigated implications of transparent mechanisms in the context of an introductory object-oriented programming course using Python. Here transparent mechanisms are those that reveal how the instance object in Python relates to its instance data. We asked students to write a new method for a provided Python class in an attempt to answer two research questions: 1) to what extent do Python's transparent OO mechanisms lead to student difficulties? and 2) what are common pitfalls in OO programming using Python that instructors should address? Our methodology also presented the correct answer to the students and solicited their comments on their submission. We conducted a content analysis to classify errors in the student submissions. We find that most students had difficulty with the instance (self) object, either by omitting the parameter in the method definition, by failing to use the instance object when referencing attributes of the object, or both. Reference errors in general were more common than other errors, including misplaced returns and indentation errors. These issues may be connected to problems with parameter passing and using dot-notation, which we argue are prerequisites for OO development in Python.

In the past six years, dozens of conference papers and journal articles have been presented in Association of Computing Machinery (ACM) and Institute of Electrical and Electronics Engineers (IEEE) educational forums concerning computing outreach activities. Nearly half of these (47.5%) appeared in SIGCSE venues. In this study, we used the free-form question "What type of data has been collected in formal, peer-reviewed research that has been conducted on computing outreach activities in recent years"? as a basis for a systematic literature review in these venues from 2009-2015. During the analysis of the articles, it was discovered that a majority of efforts focused on middle school and high school students, a majority of the reported events took place in the United States, and almost half had a goal of increasing gender diversity in computing. This paper summarizes the information about the studies, including their data collection techniques and the data that was collected. We also present a list of recommended practices for data collection, methodologies, and reporting for educational researchers engaged in these activities in an effort to provide comparative data and allow us as a community to more scientifically understand the impact that these activities are having on the participants.

A lack of diversity in the computing field has existed for several decades, and although female participation in computing remains low, outreach programs attempting to address the situation are now quite numerous. To begin to understand whether or not these past activities have had long-term impact, we conducted a systematic literature review. Upon discovering that longitudinal studies were lacking, we investigated whether undergraduate students believed that their participation in computing activities prior to college contributed to their decision to major in a computing field. From the 770 participants in the study, we discovered that approximately 20% of males and 24% of females who were required to participate in computing activities chose a computing or related major, but that males perceived that the activity had a greater affect on their decision (20%) than females (6.9%). Females who participated in an outreach activity were more likely to major in computing. Compared with females who chose to major in computing, females who did not were less likely to indicate that the majority of students participating in activities were boys and that they were a welcome part of the groups. Results also showed that female participants who do not ultimately major in computing have a much stronger negative perception of the outreach activities than male participants who also chose a non-computing major. Although many computing outreach activities are designed to diversify computing, it may be the case that, overall, boys receive these activities more favorably than girls, although requiring participation yields approximately the same net positive impact.

Over the last decade, there has been a concerted effort to bring more diverse voices to the technology field, with much of this being done through outreach activities to girls and boys. Unfortunately, data demonstrating the long-term impact of outreach activities remains rare. To contribute to knowledge on the longitudinal effect of outreach programs, we used a quantitative methodology that followed a descriptive design approach to explore the impact of participation in outreach activities on the choice of undergraduate major. Of those surveyed, 45.3% of the 770 respondents recalled participating in these activities. The results indicate that these activities had a more positive impact on Asians and more negative impact on Hispanics. Blacks/African Americans were more likely to voluntarily participate in outreach activities than Hispanics, and whites were more likely to feel that they were a welcome part of the group than non-whites. The results also may indicate that when outreach programs are available in earlier grades, they are not reaching non-white participants to the same extent as white participants.

Previous work has shown that factors such as student engagement and involvement can impact progress for computer science majors. One promising approach for improving student engagement is learning communities, which have a long history in academia but are relatively uncommon in computing. In this article we describe a linked-courses learning community for women and men of color majoring in development-focused computing degrees. We provide logistical information about the first offering of the learning community and assess the effectiveness of the community via a student survey. Our results show that students in the learning community are more likely to report that they have support for success in computer science courses and that they are a part of a community of programmers.

Student success in an introductory programing course is crucial, both because it influences retention and because student attitudes and habits in a first course can have a lasting impact on student success in computer science as a field. In this paper we present results about student attitudes and habits before and after a CS1 class. Statistically significant attitude differences were found in three areas: students were less likely to report they were good at programming, more likely to agree they are challenged by programming problems they can't understand immediately, and are less likely to report that computer science allows them to be creative. Statistically significant differences in female and first-quarter responses were also found.

One approach for helping students learn to program is the use of self-explanation assignments. In these assignments, students explain instructional materials using domain knowledge covered in the course. In this work, we describe a randomized experiment where students in an introductory programming course were given two kinds of self-explanation assignments. One randomly selected group worked on self-explanation assignments with supporting questions while the alternate group had the same self-explanation questions but no additional supporting exercises. The combined groups performed better on comparable test questions than students from the previous year, who did not use self-explanation questions. The group with supporting questions performed better than the group with no additional support. Based on our results and previous research on self explanation, we argue that embedding self-explanation questions into programming material is beneficial for students. Moreover, further gains are achieved from supporting questions that help focus their explanations.

No abstract available.

No abstract available.

In recent years there have been significant efforts to revamp undergraduate and K-12 curricula to emphasize computational thinking, a term popularized by Jeannette Wing in 2006. We describe work introducing and enhancing computational thinking activities and assessments in the middle- and high-school curriculum at the University of Chicago Lab Schools. In total six courses were altered as a part of the Computational Thinking across the Curriculum Project: middle-school and high-school computer science, and high-school Latin, graphic arts, English, and history. We detail the modifications to the curriculum and discuss the successes and challenges of the project.

The College of Computing and Digital Media (CDM) at DePaul University has recorded thousands of courses using an in-house system called Course Online (COL) since 2001. These recordings are available not only to students enrolled in online CDM courses, but also to students in traditional classrooms at CDM. In this study we analyzed survey responses and grade data to determine whether traditional students found COL recordings to be a valuable substitutional tool and whether the recordings had any impact on student performance. We found that a large majority of traditional CDM students find the recordings useful and believe that they improve performance. Somewhat counter to the students' perceptions, we found that there were no large differences in performance prior to the introduction of COL recordings and after COL recordings began to be available.

Effective student recruitment is an important issue for computing educators. We describe a mentoring program designed for prospective students at DePaul University and begin to understand the effectiveness of such a program. The program has been in place since 2004, and an initial analysis of survey data has led to changes in the way the program will be run and in how data will be collected for the next phase of the study.

Specifying file references for hypertext links is an elementary competence that nevertheless draws upon core computational thinking concepts such as tree traversal and the distinction between relative and absolute references. In this article we explore the learning effects of different instructional strategies in the context of an introductory computing course. Results suggest that asking students to do targeted tasks, albeit supported with working examples, is not the best preparation. Instead, unstructured study of examples produces superior learning. Answering targeted conceptual questions can also yield comparably positive learning but only in qualified contexts. While perhaps unintuitive, these results are consistent with a long line of research on human cognition and learning. We discuss our results in the context of this previous research and recommend effective instructional strategies, which may apply to a broad range of computational concepts.

We study student understanding of the use of a tree structure in the context of an introductory web development course. In particular, we analyze student answers as they use a tree structure to construct file references in web pages. More fundamentally, our study initiates a bottom-up study of computational thinking by identifying the computational thinking mistakes that students make when they are learning resource referencing for web development. Our preliminary results suggest that students do not necessarily learn abstract concepts (like trees) and abstract rules of reasoning (composing relative and absolute tree paths) by just working with folders and composing file references alone.

We describe a framework for implementing computational thinking in a broad variety of general education courses. The framework is designed to be used by faculty without formal training in information technology in order to understand and integrate computational thinking into their own general education courses. The framework includes examples of computational thinking in a variety of general education courses, as well as sample in-class activities, assignments, and other assessments for the courses. The examples in the different courses are related and differentiated using categories taken from Denning Great Principles of Computing, so that similar types of computational thinking appearing in different contexts are brought together. This aids understanding of the computational thinking found in the courses and provides a template for future work on new course materials. Specific examples of computational thinking in the design category are provided in the context of three distinct courses.

Designing an effective capstone course can be a challenge, particularly at a university on the quarter system. The capstone course is generally an integrative experience, designed to help students pull together skills they have learned throughout their college careers. Determining how to effectively evaluate the work that students do in a capstone course is a difficult task, particularly when the capstone is in a game development program. There are many measures of the quality of a game, some of which are less important in a curriculum focused on programming and production. Here we propose a set of metrics tailored to a game development capstone course. We consider two main metrics: technology metrics that focus the integration of standard, specific game technologies and design metrics that consider how well the implementation matches the game design at different stages of development. We also discuss several factors that we believe have contributed to success in the game development capstone course, including industry involvement as a student motivator and the use of XNA in the curriculum.

No abstract available.

No abstract available.

As educators work to expand the audience interested in computer science, computer gaming programs have blossomed at a variety of educational institutions. Educators are coming to recognize that gaming is a compelling way to motivate students to learn challenging technical concepts such as programming, software engineering, algorithms, and project management. At the core of many gaming programs are game development courses, which teach technical aspects about software development in a motivating environment. While many game development courses share a common goal, the structure and goals of game development courses can be quite diverse. We describe a game development course that uses the XNA platform to allow a heterogeneous group of students to gain experience in all aspects of console game creation, an approach we believe has some interesting pedagogical benefits.

The complexity of languages like Java and C++ can make introductory programming classes in these languages extremely challenging for many students. Part of the complexity comes from the large number of concepts and language features that students are expected to learn while having little time for adequate practice or examples. A second source of difficulty is the emphasis that object-oriented programming places on abstraction. We believe that by placing a larger emphasis on testing in programming assignments in these introductory courses, students have an opportunity for extra practice with the language, and this affords them a gentler transition into the abstract thinking needed for programming. In this paper we describe how we emphasized testing in introductory programming assignments by requiring that students design and implement tests before starting on the program itself. We also provide some preliminary results and student reactions.

Abstract The equivalence of semantic networks with spreading activation and vector spaces with dot product is investigated under ranked retrieval. Semantic networks are viewed as networks of concepts organized in terms of abstraction and packaging relations. It is shown that the two models can be effectively constructed from each other. A formal method is suggested to analyze the models in terms of their relative performance in the same universe of objects.