ACM Transactions on

Computing Education (TOCE)

Latest Articles

A Meta-Analysis of Pair-Programming in Computer Programming Courses: Implications for Educational Practice

Several experiments on the effects of pair programming versus solo programming in the context of education have been reported in the research... (more)

Writing In-Code Comments to Self-Explain in Computational Science and Engineering Education

This article presents two case studies aimed at exploring the use of self-explanations in the context of computational science and engineering (CSE)... (more)

Impact of Using Tools in an Undergraduate Software Testing Course Supported by WReSTT

Software continues to affect a major part of our daily lives, including the way we use our phones, home appliances, medical devices, and cars. The... (more)

Teaching Computational Thinking Using Agile Software Engineering Methods: A Framework for Middle Schools

Computational Thinking (CT) has been recognized as one of the fundamental skills that all graduates should acquire. For this reason, motivational... (more)

Getting IT Together: A Longitudinal Look at Linking Girls' Interest in IT Careers to Lessons Taught in Middle School Camps

The dearth of women choosing information technology (IT) careers has been identified as a national problem in the United States. Efforts have been made to combat this by educating girls at a young age about technology. Recent research demonstrates that exposure to technology is insufficient to change young girls’ attitudes towards IT careers... (more)

Early Lessons from Evaluation of Computer Science Teacher Professional Development in Google’s CS4HS Program

This article compares self-reported learning gains and experiences of teachers in four professional... (more)


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.

Special Issue on global software engineering education coming in late 2017

ACM TOCE will publish a special issue on global software engineering education in late 2017. Authors interested in submitting articles to this special issue need to submit article abstracts by  December 15, 2016, and full papers by March 15, 2017. For more information, please see the call for papers.

Special Issue on capstones and projects coming in early 2018

ACM TOCE will publish a special issue on capstones and projects in computing education in 2018. Extended abstracts for this special issue are due by January 15, 2017, and full papers by April 1, 2017. For more information, please see the call for papers.

Special Issue on learning analytics coming in early 2017

ACM TOCE will publish a special issue on learning analytics for computing education in 2017. Authors interested in submitting articles to this special issue need to submit article abstracts by May 15, 2016, and full papers by September 30. For more information, please see the call for papers.

About TOCE

The ACM Transactions on Computing Education (TOCE) publishes high quality, peer-reviewed, archival papers in computing education. Papers published in TOCE take a scholarly approach to teaching and learning, establish a clear connection to student learning, and appeal to a broad audience interested in computing education: instructors, researchers, curriculum designers, and administrators.  READ MORE

Forthcoming Articles

How Student-centered is the Computer Science Classroom? A Survey of College Faculty

Student-centered instructional practices structure a class so students interact with each other, engage deeply with the content and receive formative feedback. These evidence-based practices benefit all students but are particularly effective with underrepresented learners including women and members of other minority groups. To what extent have computer science faculty embraced these strategies? We surveyed over seven hundred U.S. faculty to find out. Results suggest female faculty, associate professors and those teaching courses with enrollment above eighty students are more likely to use these student-centered practices. Across all responses, twenty percent of faculty use student-student interaction on a regular basis during class. In contrast, thirty-eight percent of faculty rely on lecture for content delivery. Results were also compared with published data for other academic disciplines. CS faculty are less likely to use these practices compared to their non-STEM colleagues but more likely to use these practices compared to other STEM discipline faculty. Overall, CS faculty have adopted student-centered practices to some degree but our community should strive for higher adoption rates to help as many students as possible learn and remain in computer science.

A Scalable Methodology to Guide Student Teams Executing Computing Projects

This paper reports on a sequential mixed-methods research study, which compared different approaches on how to guide students through a semester long data science project. Four different methodologies, ranging from a traditional just assign some intermediate milestones to other more Agile methodologies, were first compared via a controlled experiment. The results of this initial experiment showed that the project methodology used made a significant difference in student outcomes. Surprisingly, the Agile Kanban approach was found to be much more effective than the Agile Scrum methodology. Based on these initial results, in the second semester, we focused on use of the Kanban methodology. The findings in the second, more qualitative phase, confirmed the methodologys usefulness and scalability. A key issue when using the scrum methodology was that the students had a very difficult time estimating what could be completed in each of their two-week sprints. The Kanban board, which visually shows and limits work-in-progress, was found to be an effective way for students to communicate with each other as well as with their instructor. In addition, Agile Kanban also streamlined the work required for instructors to efficiently provide guidance to student teams, and to understand each teams status. In summary, a scalable Kanban methodology, which can be applied to a wide variety of student computing projects, was found to an effective methodology to guide and manage student projects, improving student outcomes and minimizing instructor workload.

A controlled experiment on Python vs C for an Introductory Programming course: students' outcomes

We performed a controlled experiment on comparing a C versus a Python Introductory Programming course. Three faculty at our university taught the same CS1 course for the same majors in two different semesters, one version in Python and one in C, with a total of 391 students involved in the experiment. We measured dropout rate, the failure rate, the grades on the two exams, the proportion of completed lab assignments, and the number of submissions per completed assignment. There was no difference in the dropout rate. The failure rate for Python was 16.9\% against 23.1\% for C. The effect size on the comparison of Python against C on the midterm exam was 0.27, and 0.38 for the final exam. The effect size for the proportion of completed assignments is 0.39 and the effect size for the number of submissions per assignment is -0.61 (Python has less submissions per completed assignments). All effect sizes are significantly different that 0. Thus for all measures, with the exception of dropout rate, the version of the course in Python yielded better student outcomes than the version in C.

The Core Cyber-Defense Knowledge, Skills, and Abilities (KSAs) That Cybersecurity Students Should Learn in School: Results from Interviews with Cybersecurity Professionals

Our cybersecurity workforce needs surpass our ability to meet them. These needs could be mitigated by developing relevant curricula that prioritize the Knowledge, Skills, and Abilities (KSAs) most important to cybersecurity jobs. To identify the KSAs needed for performing cybersecurity jobs, we administered survey-interviews to 44 cyber professionals at the premier hacker conferences Black Hat 2016 and DEF CON 24. Questions concerned 32 KSAs related to cyber-defense. Participants rated how important each KSA was to their job and indicated where they had learned that KSA. Fifteen of these KSAs were rated as being of higher-than-neutral importance. Participants also answered open-ended questions meant to uncover additional KSAs that are important to cyber-defense work. Overall, the data suggest that KSAs related to networks, vulnerabilities, programming, and interpersonal communication should be prioritized in cybersecurity curricula.

How do Gender, Learning Goals, and Forum Participation Predict Persistence in a Computer Science MOOC?

Massive Open Online Courses (MOOCs)-in part, because of their free, flexible, and relatively anonymous nature-may provide a means for helping overcome the large gender gap in Computer Science (CS). This study examines why women and men chose to enroll in a CS MOOC and how this is related to successful behavior in the course by (a) using k-means clustering to explore the reasons why women and men enrolled in this MOOC and then (b) analyzing if these reasons are related to forum participation and, ultimately, persistence in the course. Findings suggest that women and men have different reasons for taking this CS MOOC, and they persist at different rates, an outcome which is moderated by forum participation.

Transfer Learning Methods in Programming Course Outcome Prediction

The introductory programming course is one of the very first courses that aspiring computer scientists take at a University. It is, unfortunately, also known for its low retention rates. In-time identification of those students who are likely to fail the course or to drop out would provide opportunities for early interventions. Given additional support and sufficient practice, students who might initially lean towards dropping out could be persuaded to continue study the subject. The computing education literature contains a wide variety of methods that could be used to identify students who are at risk of failing their studies, many of which are based on machine learning models that learn to make predictions based on previously observed data. However, in educational contexts, differences between courses set huge challenges for the generalizability of these methods. For example, traditional machine learning methods assume identical distribution in all data -- in our terms, that all teaching contexts are alike. In truth, data collected from different courses can be very different as there are many factors that may change, including grading, materials, teaching approach and -- for sure -- the students. Transfer learning methodologies have been created to address this challenge. They relax the strict assumption of identical distribution for training and test data, but naturally some similarity of the context is still needed for efficient learning. In this work, we review the concept of transfer learning methods especially for the purpose of the identification of students who are at risk of failing an introductory programming course, and contrast the results with those from traditional machine learning methods. The methods are evaluated using data collected in-situ from two separate introductory programming courses. The main focus is to see how these methods perform in the first weeks of the course, which are often the most critical for students. We demonstrate empirically that transfer learning methods are able to improve the predictions especially in cases with limited amount of training data, for example when making early predictions for a new context. Traditional machine learning models are, however, also sufficiently accurate assuming the contexts are closely related and the features describing the student activity are carefully chosen to be insensitive to the fine differences.

Involving External Stakeholders in Project Courses

Problem: The involvement of external stakeholders in capstone projects and project courses is desirable due to its potential positive effects on the students. Capstone projects particularly profit from the inclusion of an industrial partner to make the project relevant and help students acquire professional skills. In addition, an increasing push towards education that is aligned with industry and incorporates industrial partners can be observed. However, the involvement of external stakeholders in teaching moments can create friction and could, in the worst case, lead to frustration of all involved parties. Contribution: We developed a model that allows analysing the involvement of external stakeholders in university courses both in a retrospective fashion to gain insights from past course instances and in a constructive fashion to plan the involvement of external stakeholders. Key Concepts: The conceptual model and the accompanying guideline guide the teachers in their analysis of stakeholder involvement. The model is comprised of several activities (define, execute, and evaluate the collaboration) and the guideline provides questions that the teachers should answer for each of these activities. In the constructive use, the model allows the teachers to define an action plan based on an analysis of potential stakeholders and the pedagogical objectives. In the retrospective use, the model allows the teachers to identify the issues that appeared during the project and which causes were underlying the issues. Drawing from ideas of the reflective practitioner, it contains an emphasis on reflection and interpretation of the observations made by the teacher and other groups involved in the courses. Key Lessons: Applying the model retrospectively to a total of eight courses reveals that it is possible to reveal so far implicit risks and assumptions and to gain a better insight into interaction between the external stakeholder and the students. The empirical data has revealed seven recurring risk themes that categorise the different risks that appeared in the analysed courses. These themes can also be used to categorise mitigation strategies to address these risks proactively. Additionally, aspects not related to external stakeholders, e.g., about the interaction of the project with other courses in the study program, have been revealed. The constructive use of the model for one course has proved helpful in identifying action alternatives and finally deciding to not include external stakeholders in the project due to the perceived cost-benefit-ratio. Implications to practice: Our evaluation shows that the model is a viable and useful tool that allows teachers to reason about and plan the involvement of external stakeholders in a variety of course settings, and in particular in capstone projects.

Developing Computational Thinking Through a Virtual Robotics Programming Curriculum

Computational Thinking describes key principles from computer science that are broadly generalizable. Robotics programs can be engaging learning environments for acquiring core computational thinking competencies. However, few empirical studies evaluate the effectiveness of a robotics programming curriculum for developing broader computational thinking practices and skills. This study measures pre-post gains with new computational thinking assessments given to middle-school students who participated in a virtual robotics programming curriculum. Overall, participation in the virtual robotics curriculum was related to significant gains in pre- to post-test scores, with larger gains in students who made further progress through the curriculum. The success of this intervention suggests that participation in a scaffolded programming curriculum, within the concrete context of virtual robotics, supports the development of generalizable computational thinking skills that are associated with increased problem solving performance on non-robotics computing tasks. However, rate of progress through such a curriculum is a challenge for many teachers.

Peer Review in CS2: Conceptual Learning and High-Level Thinking

In computer science, students could benefit from exposure to critical programming concepts from multiple perspectives. Peer review is one method to allow students to experience authentic uses of the concepts in an activity that is not itself programming. In this work, we examine how to implement the peer review process in early, object-oriented, computer science courses as a way to increase the students knowledge of programming concepts, specifically Abstraction, Decomposition, and Encapsulation, and to develop their higher-level thinking skills. We are exploring the peer review process, the effects of the type of review on the reviewers, and the results this has on the students learning. To study these ideas, we used peer review activities in CS2 classes at two universities over the course of a semester. Using three groups (one reviewing their peers, one reviewing the instructor, and one completing small design or coding assignments), we measured the students conceptual understanding throughout the semester with concept maps and the reviews they completed. We found that reviewing helped students learn Decomposition, especially those reviewing the instructors programs, but we did not find that it improved the students level of thinking. Overall, reviews (peer or otherwise) are beneficial for teaching Decomposition to CS2 students and can be used as an alternative method for teaching other object-oriented programming concepts.

Software Theater -- Teaching Demo Oriented Prototyping

Modern capstone courses use agile methods to deliver and demonstrate software early in the project. However, a simple demonstration of functional and static aspects does not provide real-world software usage context, although this is integral to understand software requirements. Software engineering is experimental knowledge work: it involves creativity, imagination and interaction, that are typically not emphasized in its education. Therefore, a more engaging, dynamic way of presenting software prototypes is needed that creates a basis for communication about requirements and the context in which the software is used. We combine agile methods, scenario-based design and theatrical aspects into software theater, an approach to present visionary scenarios using techniques borrowed from theater and film, including props and humor. In this article, we describe our approach and provide examples and patterns to demonstrate its potential. We present two large case studies in which we teach students with varying levels of experience to apply software theater: a capstone course involving industrial customers with 100 students and an interactive lecture-based course with 400 students. We empirically evaluated the use of software theater in both courses using quantitative and qualitative methods. Our evaluations show that students understand and apply software theater and that this technique increases their motivation to prepare demonstrations already early in the project. Software theater demonstrations are more creative, memorable, dynamic and engaging than traditional techniques and bring fun into education.

A Multi-Institutional Perspective on H/FOSS Projects in the Computing Curriculum

Many computer science programs have capstone project courses which allow students to integrate knowledge from the full breadth of their major. Capstone projects may be student designed, instructor designed, designed in conjunction with outside companies, or integrated with ongoing free and open source (FOSS) projects. The FOSS approach has attracted a great deal of interest, in particular when integrated with projects that have humanitarian goals (HFOSS). There is literature that indicates that HFOSS projects increase student engagement and interest. However, instructors who wish to adopt an open source approach may worry that they cannot adapt this approach to the specific needs and goals of their institution and students. In this paper, we describe five unique models for incorporating significant FOSS or HFOSS (``H/FOSS'') projects into capstone project courses, from five distinct types of institution. All of the models presented are based on sustained H/FOSS engagement with projects that last at least one semester. The goal is to provide a guide for instructors wondering how to integrate significant H/FOSS project work into their curriculum. Each model is described in terms of its characteristics and how it fits the needs of the institution using the model. Assessment of each model is also presented. We then discuss the themes that are common across the models, such as project selection, team formation, mentoring, and student assessment. We examine the choices made by each model, as well as the challenges faced. We end with a discussion of initiatives that leverage institutional efforts by collaborating with outside organizations in order to address the challenges of these projects.


Publication Years 2001-2017
Publication Count 311
Citation Count 1939
Available for Download 310
Downloads (6 weeks) 3069
Downloads (12 Months) 25344
Downloads (cumulative) 291291
Average downloads per article 940
Average citations per article 6
First Name Last Name Award
El Saddik Abdulmotaleb ACM Distinguished Member (2010)
ACM Senior Member (2008)
Joel Adams ACM Distinguished Member (2012)
ACM Senior Member (2011)
Douglas Baldwin ACM Senior Member (2012)
Catriel Beeri ACM Fellows (2007)
Mordechai Ben-Ari ACM Distinguished Member (2009)
Amy S Bruckman ACM Senior Member (2009)
Peter Brusilovsky ACM Senior Member (2008)
Martin C Carlisle ACM Distinguished Member (2009)
ACM Senior Member (2006)
John M Carroll ACM Fellows (2003)
Michael E. Caspersen ACM Distinguished Member (2013)
ACM Senior Member (2011)
Lillian N Cassel ACM Distinguished Member (2012)
ACM Senior Member (2011)
Hsinchun Chen ACM Fellows (2015)
John Cigas ACM Senior Member (2015)
Steve Cooper ACM Distinguished Member (2012)
ACM Senior Member (2009)
Adrienne Decker ACM Senior Member (2016)
Stephen H Edwards ACM Distinguished Member (2014)
Barbara Jane Ericson ACM Senior Member (2016)
Barbara Ericson ACM Karl V. Karlstrom Outstanding Educator Award (2010)
Yishai Feldman ACM Senior Member (2007)
Sally Fincher ACM Distinguished Member (2009)
Daniel D Garcia ACM Distinguished Member (2012)
Mark Guzdial ACM Distinguished Member (2014)
ACM Fellows (2014)
ACM Karl V. Karlstrom Outstanding Educator Award (2010)
ACM Senior Member (2009)
David Harel ACM Software System Award (2007)
ACM Fellows (1994)
ACM Karl V. Karlstrom Outstanding Educator Award (1992)
Lance Hoffman ACM Fellows (1995)
Jhilmil Jain ACM Senior Member (2014)
Mike Joy ACM Senior Member (2009)
Randy H. Katz ACM Karl V. Karlstrom Outstanding Educator Award (1999)
ACM Fellows (1996)
Amruth Kumar ACM Distinguished Member (2016)
ACM Senior Member (2009)
Deepak Kumar ACM Senior Member (2009)
Michael Kölling ACM Distinguished Member (2011)
Richard E. Ladner ACM Fellows (1995)
George Lepouras ACM Senior Member (2008)
Monica McGill ACM Senior Member (2016)
Filippo Menczer ACM Distinguished Member (2013)
Gail C Murphy ACM Distinguished Member (2010)
David Patterson ACM-IEEE CS Eckert-Mauchly Award (2008)
ACM Distinguished Service Award (2007)
ACM Fellows (1994)
ACM Karl V. Karlstrom Outstanding Educator Award (1991)
Manuel A. Perez-Quinones ACM Senior Member (2017)
Leo Porter ACM Senior Member (2017)
Hridesh Rajan ACM Senior Member (2014)
Clifford A Shaffer ACM Distinguished Member (2015)
ACM Senior Member (2007)
Shervin Shirmohammadi ACM Senior Member (2017)
Ralf Steinmetz ACM Fellows (2001)
Chris Stephenson ACM Presidential Award (2016)
ACM Senior Member (2009)
Bent Thomsen ACM Senior Member (2016)
Tammy VanDeGrift ACM Senior Member (2011)
J. Angel Velazquez-Iturbide ACM Senior Member (2016)
Henry M Walker ACM Distinguished Member (2009)
ACM Senior Member (2009)
Laurie Ann Williams ACM Distinguished Member (2011)

First Name Last Name Paper Counts
Josh Tenenberg 13
Robert McCartney 13
Michal Armoni 7
Mordechai Ben-Ari 5
Christopher Hundhausen 5
Michael Kölling 4
Deepak Kumar 4
Mark Guzdial 4
Mary Rosson 3
Stephen Edwards 3
Tammy VanDeGrift 3
Ville Karavirta 3
Peter Brusilovsky 3
Jürgen Börstler 3
Mike Joy 3
Brian Hanks 3
Michail Giannakos 3
Ian Utting 3
Peter Hubwieser 3
Jesús Velázquez-Iturbide 3
William Yurcik 3
Barry Fagin 2
B Popovsky 2
Craig Miller 2
Orit Hazzan 2
Adam Carter 2
Anthony Robins 2
John Maloney 2
Brian Dorn 2
Craig Zilles 2
Shuchi Grover 2
Ari Korhonen 2
Guido Rößling 2
Grant Braught 2
Rachelle Heller 2
Abdulmotaleb El Saddik 2
Ville Tirronen 2
Sally Fincher 2
Chris Stephenson 2
Neil Brown 2
Amy Bruckman 2
Holly Yanco 2
Lisa Meeden 2
Deborah Frincke 2
Ville Isomöttönen 2
Stephen Cooper 2
Lisa Kaczmarczyk 2
Michael, Loui 2
James Paterson 2
John Carroll 2
Tom Mcklin 2
Douglas Blank 2
S Oudekirk 2
Paul Gestwicki 2
Thomas Hilburn 2
Edward Fox 2
Richard Conn 2
Linda Werner 2
Orni Meerbaum--Salant 2
Albert Ritzhaupt 2
Tariq King 2
Deborah Fields 2
Monica McGill 2
Ralf Steinmetz 2
Martin Carlisle 2
Amruth Kumar 2
Amber Settle 2
Juha Sorva 2
Sergey Sosnovsky 2
Peter Clarke 2
Richard Ladner 2
Yasmin Kafai 2
Doug Baldwin 2
Stefan Fischer 2
Hsinchun Chen 2
Colin Higgins 2
Mitchel Resnick 2
Alejandra Magana 2
Michael Falk 2
Debra Davis 2
Geoffrey Herman 2
Lauri Malmi 2
Lecia Barker 2
Joanna Goode 2
Alyce Brady 2
Russell Boyatt 2
Andrea Lawrence 1
Tricia Shepherd 1
Cynthiabailey Lee 1
Weijia Shang 1
Sarah Buchanan 1
Susanne Hambrusch 1
Tim Wahls 1
Jane Margolis 1
Amjad Altadmri 1
Letizia Jaccheri 1
Demetrios Sampson 1
Carol Martin 1
R Maly 1
Ajay Gupta 1
Chris Wild 1
Kurt Rothermel 1
Allison Tew 1
Martín Llamas-Nistal 1
Manuel Caeiro-Rodríguez 1
Juan Santos Gago 1
Thorsten Hampel 1
Wesley Coelho 1
David Hendry 1
Robert Gay 1
Carl Burch 1
Oliver Buhn 1
Thomas Röblitz 1
Paul Kuban 1
Rammohan Ragade 1
Philippas Tsigas 1
Manuel Pérez-Quiñones 1
Athanasios Tsintsifas 1
Geoffrey Gray 1
Beth Simon 1
Jorma Sajaniemi 1
Bradley Pascoe 1
Cheston Williams 1
Lance Hoffman 1
Uolevi Nikula 1
Jonas Boustedt 1
Shannon Campe 1
Tal Hassner 1
Susan Reardon 1
Brendan Tangney 1
Stephen Chan 1
Hongva Leong 1
Nichole Turnage 1
Natalie Rusk 1
Michael Yudelson 1
Ricky Archer 1
Nickolas Falkner 1
Brian McNely 1
Nabil El Ioini 1
Zdravko Markov 1
Michael Stewart 1
Mohsen Beheshti 1
Sheila Humphreys 1
Tom Murphy 1
Yasser Elleithy 1
Randy Katz 1
David Patterson 1
Peter Andreae 1
Roland Mittermeir 1
Françoise Tort 1
Barbara Ericson 1
Javier Muguerza 1
Bent Thomsen 1
Michael Caspersen 1
Joseph Hollingsworth 1
Daniel Zingaro 1
Amit Shesh 1
Siddharth Kaza 1
Erno Lokkila 1
Catharine Brand 1
Julie Rursch 1
Doug Jacobson 1
Kian Pokorny 1
Alexander Chizhik 1
Stanisław Radziszowski 1
Joseph LaViola, 1
Eunkyoung Lee 1
L Eby 1
Konstantinos Chorianopoulos 1
Nicolas Georganas 1
Hongchi Shi 1
Gail Murphy 1
Zan Huang 1
Kelly Schultz 1
Keith Shomper 1
Martin Shepperd 1
Kenneth Hoganson 1
Laurie Williams 1
Marcus Brown 1
Yishai Feldman 1
Gary Nutt 1
Frank Greitzer 1
Olga Kuchar 1
Nathan Griffiths 1
Christopher Douce 1
Michele Jackson 1
Dilvan Moreira 1
Warren Harrison 1
Vince Delio 1
Peter Bloniarz 1
Sergio Daicz 1
Cecile Yehezkel 1
Stuart Hirshfield 1
Timothy Gegg-Harrison 1
Michael Grinder 1
Robert Allen 1
Kay Robbins 1
Theodora Koulouri 1
Matti Lattu 1
Brian Silverman 1
Vladimir Zadorozhny 1
Yaseen Qadah 1
Linda Marshall 1
David Largent 1
Roberto d’Amore 1
Carsten Schulte 1
Susan Coleman 1
V Renumol 1
John Haddow 1
Sarah Hug 1
Orpheus Crutchfield 1
Dennis Brylow 1
Anastasios Theodoropoulos 1
Tim Bell 1
Igor Semakin 1
Luisa Zecca 1
Fraser McKay 1
Isabel Dietrich 1
Marie Bienkowski 1
Nicholas Diana 1
Debbie Richards 1
Niko Myller 1
Jason Hallstrom 1
Lauri Malmi 1
Michael Reese 1
Tanya McGill 1
Leonardo Mariani 1
Jason Freeman 1
Sangjin An 1
Arto Vihavainen 1
Kris Gutierrez 1
Ian Horses 1
Ashok Basawapatna 1
Jairo Pava 1
Paul Krause 1
Kristian Sandahl 1
Judith Mann 1
Anne Spence 1
Henry Walker 1
A Brady 1
Leland Beck 1
Michael Bruce-Lockhart 1
Marcin Łukowiak 1
James Vallino 1
Eliot Kaplan 1
Neomi Liberman 1
Mike Joy 1
Dongyong Zhang 1
Achilles Kameas 1
Charles Overstreet 1
Agustín González 1
Torsten Leidig 1
Lillian Cassel 1
Jeffrey Humphries 1
Luis Anido-Rifón 1
N Barnette 1
Sushing Chen 1
Raymond Mcdowell 1
Geoffrey Roy 1
Emilio Luque 1
Peter McKenna 1
Sarah Berenson 1
Falko Kuester 1
Leenkiat Soh 1
Gwen Nugent 1
Marja Kuittinen 1
Andreas Zendler 1
Avi Cohen 1
Rose Shumba 1
Jon Hobbs 1
Thomas Hurbanek 1
Jose Galaviz 1
Murray Pearson 1
Bhagyavati 1
Jussi Kasurinen 1
Carol Zander 1
Wanda Kunkle 1
Jill Denner 1
Itzik Bayaz 1
Christophe Kolski 1
Xin Zhou 1
Huiming Yu 1
Camilo Vieira 1
Alana Platt 1
Kacie Conroy 1
Juliane Blazevski 1
Abdulhadi Shoufan 1
Sorin Huss 1
Paul Gross 1
Dharanipragada Janakiram 1
Audrey Rorrer 1
Guy Haas 1
Peter Khooshabeh 1
Stephanie Ludi 1
Thomas Reichlmayr 1
Viggo Kann 1
Masaki Ishiyama 1
George Lepouras 1
Dario Malchiodi 1
Sue Sentance 1
Rosalie Ocker 1
Richard Pak 1
Murali Sitaraman 1
Andreas Stefik 1
Daniela Micucci 1
Brian Magerko 1
Mike Reilly 1
Elise Livingston 1
Andrea Crews-Brown 1
Blair Taylor 1
Shingshin Shin 1
Jeongwon Choi 1
Ulrik Schroeder 1
Raghu Raman 1
Giora Alexandron 1
David Harel 1
Edward Jones 1
Simone Kauffeld 1
Bernd Bruegge 1
Stephan Krusche 1
Thomas Clayton 1
Cynthia Wambsgans 1
Mary Switzer 1
Andrea Danyluk 1
Scott Grissom 1
Christopher Wood 1
Chris Mayfield 1
John Korb 1
Debora Lui 1
Ilias Pappas 1
Nuzi Haneef 1
Sonja Gievska-Krliu 1
X Zhu 1
Cora Burger 1
Shervin Shirmohammadi 1
Michael Evans 1
Taneshia Marshall 1
William Gilley 1
Mark Holliday 1
Julia Lobur 1
Chao Teo 1
B Dugan 1
Cynthia Lester 1
Mark Warschauer 1
Svetlana Yarosh 1
Ching Shene 1
Igor Verner 1
Christopher Kitts 1
Adnan Baykal 1
Robert Bangert-Drowns 1
Sandoor Schuman 1
Wenjung Hsin 1
Paul Wagner 1
José Brustoloni 1
M Koger 1
Timothy Yuen 1
Vincent Ng 1
Marisa Exter 1
Michael O’Grady 1
Peter Alston 1
Xiaohong Yuan 1
Percy Vega 1
Lisa Thompson 1
Richard Alo 1
Colleen Lewis 1
Dan Garcia 1
Kathleen Goldschmidt 1
Jeongkyu Lee 1
Angeliki Antoniou 1
Mattia Monga 1
Béatrice Drot-Delange 1
Monique Grandbastien 1
José Martín 1
Olusola Adesope 1
Satabdi Basu 1
Michael Eagle 1
Julie Barnes 1
Maria Knobelsdorf 1
Dieter Engbring 1
Krishnashree Achuthan 1
Sandeep Mitra 1
Lori Postner 1
Hilko Paulsen 1
Wei Zhang 1
Khaled Benkrid 1
Ursula Wolz 1
Jane Margolis 1
Robert Drysdale 1
Karen Renaud 1
Quintin Cutts 1
Pawan Agarwal 1
Jhilmil Jain 1
Theodore Norvell 1
Pierluigi Crescenzi 1
Alfinge Wang 1
Beverley Cook 1
Laurence Merkle 1
Simon Rawles 1
Ronghua Wang 1
Fushing Sun 1
William Leahy 1
Sarita Yardi 1
Reinhard Keil-Slawik 1
Linda Null 1
Michael Chau 1
David Ginat 1
Byron Marshall 1
Juan Moure 1
Kathy Garvin-Doxas 1
Chihwei Ho 1
Boris Koldehofe 1
Douglas Grimes 1
Tara Hutchinson 1
Pavlos Symeonidis 1
Jussi Nikander 1
James Orwell 1
William Waite 1
Steve Carr 1
Elaine Silva 1
Michael Peterson 1
Simon Parsons 1
Elizabeth Sklar 1
Jagdish Gangolly 1
Dale Skrien 1
Luis De Simoni 1
Gabriel Wainer 1
Klaus Sutner 1
Andrew Phillips 1
Brett Landry 1
Kate Sanders 1
Claudia Ott 1
Kerry Shephard 1
Tomi Pasanen 1
Yulei(Gavin) Zhang 1
David Walsh 1
Daniellehyunsook Lee 1
Rebecca Vivian 1
Vreda Pieterse 1
R Garcia 1
Ilenia Fronza 1
Luis Corral 1
S Jayaprakash 1
Arnold Pears 1
Heather Thiry 1
Mukkai Krishnamoorthy 1
Emma Enström 1
Raissa Relator 1
Carlo Bellettini 1
Mauro Torelli 1
Tom Crick 1
Georges Baron 1
Shelly Engelman 1
Iratxe Soraluze 1
Txelo Ruiz-Vazquez 1
Lone Thomsen 1
Arto Hellas 1
John Stamper 1
Erkki Sutinen 1
Barry Ip 1
Laura Leventhal 1
Tony Koppi 1
Marco Thomas 1
Nadia Repenning 1
David Webb 1
Fred Gluck 1
Arwa Allinjawi 1
David Broman 1
Olga Liskin 1
David Johnson 1
Kimberly Misa-Escalante 1
Jiangjiang Liu 1
Meredith Stone 1
Sarah Pulimood 1
Penny Rheingans 1
Anne Brodsky 1
Joel Adams 1
Helen Hu 1
Saturnino Garcia 1
Leo Porter 1
T Hendrix 1
Ruth Davis 1
Kristin Searle 1
Judy Goldsmith 1
Nicholas Mattei 1
Jeanjinsun Ryoo 1
Ayman Abdel Hamid 1
Boris Muzykantskii 1
Wenliang Du 1
J Rodriguez-Estevez 1
Robin Adams 1
Emre Tunar 1
Osman Balci 1
Rao Shen 1
Marina Papatriantafilou 1
Kristy Huston 1
Donald Chinn 1
Victoria Sakhnini 1
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Susan Imberman 1
Laura Iwan 1
Sanjay Goel 1
George Berg 1
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Evelyn Eastmond 1
Randy Connolly 1
Jinsheng Xu 1
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Raymond Chang-Lau 1
Kenneth Goldman 1
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Tiffany Barnes 1
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Christopher Harrison 1
Manuel Carro 1
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Daiki Isayama 1
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Inga Skogh 1
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Alireza Ahadi 1
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Erkki Kaila 1
Johannes Magenheim 1
Torsten Brinda 1
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Alexander Repenning 1
Prema Nedungadi 1
Andy Luse 1
Hana Al-Nuaim 1
Robert Pastel 1
Marika Seigel 1
Alex Mayer 1
Klara Benda 1
Antonio Fuentes 1
Charles Kelemen 1
Anukrati Agrawal 1
David Umphress 1
Larry Barowski 1
Aman Yadav 1
Georgina Cosma 1
Alexandros Merkouris 1
Hussein Abdel-Wahab 1
Pamela Krolikowski 1
Ambikesh Jayal 1
Frank Mueller 1
Dolores Rexachs 1
David Livingstone 1
Christian Spannagel 1
Amer Diwan 1
Jason Gilder 1
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Neil Quinn 1
Peter Stone 1
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Dean Armstrong 1
Alberto Segre 1
Joshua Cogliati 1
Orlena Gotel 1
Anna Eckerdal 1
Lynda Thomas 1
Stanislao Lauria 1
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Bénédicte Talon 1
Thomas Park 1
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Katrina Falkner 1
Hamid Tarmazdi 1
Jason Ravitz 1
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Ulrich Kiesmuller 1
John Fernandez 1
Jason Sanchez 1
Hansa Sinha 1
Daniel Garcia 1
Koichi Yamazaki 1
Evgeniy Khenner 1
Anna Morpurgo 1
Peter Dolog 1
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Gene Poor 1
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Scott Mccoid 1
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Youngjun Lee 1
Jan Vahrenhold 1
Jaakko Kurhila 1
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Smrithi Venkatasubramanian 1
Gregory Hislop 1
Stoney Jackson 1
Tyler Sondag 1
Hridesh Rajan 1
Thomas Zimmerman 1
Karen Kim 1
Amy Fann 1
Kim Pearson 1
Robert Cupper 1
James Cross 1
Lacey Montgomery 1
Teena Vellaramkalayil 1
Stefan Schaeckeler 1
Jaime Urquiza-Fuentes 1
Ninger Zhou 1
Marie Nordström 1
Catriel Beeri 1
Yifat Ben-David Kolikant 1
Jane Sinclair 1
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Sahar Ghanem 1
William Griswold 1
Manuel Fernández-Iglesias 1
Yi Shang 1
John Zahorjan 1
Brian Shelburne 1
Kelli Slaten 1
Charles McDowell 1
Scott Turner 1
Ashok Samal 1
Taina Tikansalo 1
Jacob Dickerson 1
Jean Mayo 1
Travis Doom 1
Damira Pon 1
Matt Bishop 1
Filippo Menczer 1
John Cigas 1
Rocky Ross 1
Timothy Rosenberg 1
Andrea Forte 1
Gary Westhead 1
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Jens Bennedsen 1
Cinda Heeren 1
Ingrid Russell 1
Todd Neller 1
Alexander Alon 1
Monika Akbar 1
Sean Ponce 1
Ron Eglash 1
Andrew Woodbridge 1
Kimberly Buch 1
Julio Mariño 1
Ariel Rabkin 1
Charles Reiss 1
Michael Ziwisky 1
Violetta Lonati 1
Edurne Larraza-Mendiluze 1
Nestor Garay-Vitoria 1
Michael Giang 1
Starr Hiltz 1
Svetlana Drachova 1
Joan Krone 1
Paul Albee 1
Monica McGill 1
Adrienne Decker 1
Einari Kurvinen 1
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Ryan Grover 1
Kyuhan Koh 1
Susan Miller 1
Michal Gordon 1
Heidi Ellis 1
Maria Vasilevskaya 1
Kurt Schneider 1
Lukas Alperowitz 1
Peggy Doerschuk 1
Jill Scheibler 1
Kim Bruce 1

Affiliation Paper Counts
Villanova University 1
Calvin College 1
University of North Florida 1
College of Saint Benedict Saint John's University 1
University of Erlangen-Nuremberg 1
Anglia Ruskin University 1
University of Macedonia 1
Oklahoma Baptist University 1
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Texas A and M University - Corpus Christi 1
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Mount Royal College 1
Victoria University of Wellington 1
Bar-Ilan University 1
Henan Agricultural University 1
Lockheed Martin Corporation 1
Ecole Normale Superieure de Cachan 1
University College Dublin 1
Tel Aviv University 1
Colby College 1
Oklahoma State University - Stillwater 1
The University of Hong Kong 1
Pomona College 1
Rhode Island College 1
SUNY Brockport 1
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College of Staten Island 1
Southern Polytechnic State University 1
Dartmouth College 1
IBM Research 1
University of Dublin, Trinity College 1
Denison University 1
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The Interdisciplinary Center Herzliya 1
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Oregon State University 1
Ionian University 1
University of Florida 1
Skidmore College 1
University of Duisburg-Essen 1
University of California, Davis 1
University Southern Indiana 1
University of Washington-Bothell 1
RWTH Aachen University 1
University of Toronto 1
Yonsei University 1
Carleton University 1
Indiana University Southeast 1
Elon University 1
Rose Hulman Institute Technology 1
Park University 1
University of Nebraska at Omaha 1
Indiana University of Pennsylvania 1
Macquarie University 1
Alpen-Adria-Universität Klagenfurt 1
Kennesaw State University 1
University of Canterbury 1
University of Louisville 1
Winona State University 1
University of Liverpool 1
University of Surrey 1
Indiana University 1
Williams College 1
New York University 1
University of Florence 1
Manchester Metropolitan University 1
University of Montana 1
Messiah College 1
Wittenberg University 1
Washington University in St. Louis, School of Medicine 1
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Trinity College Hartford 1
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University of North Texas 1
Dickinson College, Pittsburgh 1
University of Strathclyde 1
University of Alabama 1
Grand Valley State University 1
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Florida Agriculture and Mechanical University 1
Rockhurst University 1
Grinnell College 1
Universite Paris Descartes 1
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Dun Laoghaire Institute of Art, Design, and Technology 1
University of Aarhus 1
Gettysburg College 1
University of Hull 1
Aberystwyth University 1
Free University of Berlin 1
University of Gavle 1
Curtin University of Technology, Perth 1
University of Nevada, Las Vegas 1
Illinois State University 1
Central Connecticut State University 1
North Dakota State University 1
University of Huddersfield 1
Zuse Institute Berlin 1
TU Dortmund University 1
California State University 1
University of Puerto Rico-Mayaguez 1
Amrita Vishwa Vidyapeetham University 1
AgentSheets, Inc 1
University of Houston-Downtown 1
Cardiff Metropolitan University 1
Universite de Lorrain 1
Edith Cowan University, Joondalup 1
CSIRO Data61 1
Ramapo College of New Jersey 2
University of Glasgow 2
University of Texas at San Antonio 2
Towson University 2
University of Waikato 2
King Abdulaziz University 2
Westminster College, Salt Lake City 2
Gottfried Wilhelm Leibniz Universitat 2
Nanyang Technological University 2
University of Wisconsin Eau Claire 2
Nottingham Trent University 2
University of Wisconsin Whitewater 2
Western Carolina University 2
Technical University in Braunschweig 2
University of Sao Paulo 2
Linkoping University 2
Central Michigan University 2
Washington University in St. Louis 2
The University of British Columbia 2
State University of New York at Albany 2
Fraunhofer Institute for Integrated Publication and Information Systems Institute 2
University of Oregon 2
Stanford University 2
University of Texas at Austin 2
Lappeenranta University of Technology 2
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Hamilton College 2
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State University of New York Geneseo 2
University of Kentucky 2
Blekinge Institute of Technology 2
San Diego State University 2
Memorial University of Newfoundland 2
Murdoch University 2
Humboldt State University 2
University of Central Florida 2
Northern Arizona University 2
Brooklyn College 2
Perm State University 2
University of Technology Sydney 2
University of Iowa 2
Microsoft Corporation 2
University of Edinburgh 2
Embry Riddle Aeronautical University 2
University of Ottawa, Canada 2
Syracuse University 2
Umea University 2
Utah State University 2
National Autonomous University of Mexico 2
Kingston University 2
University of Massachusetts Lowell 2
Hellenic Open University 2
Chalmers University of Technology 3
University of Buenos Aires 3
Swarthmore College 3
University of Peloponnese 3
Bradley University 3
University of Portland 3
Johns Hopkins University 3
University of Missouri-Columbia 3
Glasgow Caledonian University 3
Hebrew University of Jerusalem 3
Free University of Bozen-Bolzano 3
University of Arizona 3
Lamar University 3
Illinois Wesleyan University 3
University of Milan - Bicocca 3
Drexel University 3
Marquette University 3
Fort Lewis College 3
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Korea National University of Education 3
University of Pretoria 3
Aalborg University 3
Open University of Israel 3
Universidad Autonoma de Barcelona 3
University of California, Santa Cruz 3
Rensselaer Polytechnic Institute 3
Indian Institute of Technology, Madras 3
University of Nebraska - Lincoln 3
Penn State Harrisburg 3
Clemson University 3
Technical University of Madrid 3
Communaute d'Universites et d'Etablissements Lille Nord de France 3
SRI International 4
Royal Institute of Technology 4
Uppsala University 4
Iowa State University 4
University of Pennsylvania 4
University of Turku 4
The University of North Carolina at Charlotte 4
University of California, Irvine 4
Hong Kong Polytechnic University 4
University of Adelaide 4
Gunma University 4
University of Otago 4
Wright State University 4
Universidad Rey Juan Carlos 4
University of Paderborn 4
University of Maryland, Baltimore County 4
DePaul University 4
University of California, Los Angeles 4
Carnegie Mellon University 4
Ball State University 4
University of California, San Diego 4
University of Jyvaskyla 4
University of Bridgeport 4
North Carolina State University 5
The College of New Jersey 5
Montana State University 5
Santa Clara University 5
Kalamazoo College 5
University of Nottingham 5
Brunel University London 5
Technion - Israel Institute of Technology 5
University of Helsinki 6
George Washington University 6
Auburn University 6
Norwegian University of Science and Technology 6
North Carolina Agricultural and Technical State University 6
Bryn Mawr College 6
Technical University of Munich 6
USAF Academy 6
Universidad de Vigo 6
University of the Basque Country 6
University of Milan 6
University of Eastern Finland 6
University of Illinois at Urbana-Champaign 7
Pennsylvania State University 7
Rochester Institute of Technology 7
Florida International University 7
Michigan Technological University 7
Massachusetts Institute of Technology 7
Pacific Northwest National Laboratory 7
Technical University of Darmstadt 8
Old Dominion University 9
Purdue University 9
Washington State University Pullman 9
University of Washington, Seattle 10
University of Pittsburgh 10
University of California, Berkeley 10
Aalto University 11
University of Washington, Tacoma 12
The University of Warwick 12
University of Kent 13
University of Connecticut 13
Georgia Institute of Technology 17
Weizmann Institute of Science Israel 18
Virginia Tech 18
University of Colorado at Boulder 19

ACM Transactions on Computing Education (TOCE)

Volume 17 Issue 4, September 2017
Volume 17 Issue 3, August 2017 Special Issue on Learning Analytics
Volume 17 Issue 2, June 2017
Volume 17 Issue 1, January 2017

Volume 16 Issue 4, October 2016
Volume 16 Issue 3, June 2016
Volume 16 Issue 2, March 2016
Volume 16 Issue 1, February 2016

Volume 15 Issue 4, December 2015 Special Issue on Team Projects in Computing Education
Volume 15 Issue 3, September 2015
Volume 15 Issue 2, May 2015 Special Issue II on Computer Science Education in K-12 Schools
Volume 15 Issue 1, March 2015 Special Issue on Web Development
Volume 14 Issue 4, February 2015

Volume 14 Issue 3, November 2014
Volume 14 Issue 2, June 2014 Special Issue on Computing Education in (K-12) Schools
Volume 14 Issue 1, March 2014

Volume 13 Issue 4, November 2013
Volume 13 Issue 3, August 2013 Special Issue on Alternatives to Lecture in the Computer Science Classroom
Volume 13 Issue 2, June 2013
Volume 13 Issue 1, January 2013

Volume 12 Issue 4, November 2012
Volume 12 Issue 3, July 2012
Volume 12 Issue 2, April 2012
Volume 12 Issue 1, March 2012

Volume 11 Issue 4, November 2011
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Volume 11 Issue 1, February 2011

Volume 10 Issue 4, November 2010
Volume 10 Issue 3, August 2010
Volume 10 Issue 2, June 2010
Volume 10 Issue 1, March 2010
Volume 9 Issue 4, January 2010

Volume 9 Issue 3, September 2009
Volume 9 Issue 2, June 2009 Special Issue on the 5th Program Visualization Workshop (PVW’08)
Volume 9 Issue 1, March 2009
Volume 8 Issue 4, January 2009

Volume 8 Issue 3, October 2008
Volume 8 Issue 2, June 2008
Volume 8 Issue 1, March 2008
Volume 7 Issue 4, January 2008

Volume 7 Issue 3, November 2007
Volume 7 Issue 2, June 2007
Volume 7 Issue 1, March 2007

Volume 6 Issue 4, December 2006
Volume 6 Issue 3, September 2006
Volume 6 Issue 2, June 2006
Volume 6 Issue 1, March 2006

Volume 5 Issue 4, December 2005
Volume 5 Issue 3, September 2005
Volume 5 Issue 2, June 2005
Volume 5 Issue 1, March 2005

Volume 4 Issue 4, December 2004
Volume 4 Issue 3, September 2004 Special issue on robotics in undergraduate education. Part 2
Volume 4 Issue 2, June 2004 Special issue on robotics in undergraduate education. Part 1
Volume 4 Issue 1, March 2004 Special Issue on Gender-Balancing Computing Education

Volume 3 Issue 4, December 2003
Volume 3 Issue 3, September 2003
Volume 3 Issue 2, June 2003
Volume 3 Issue 1, March 2003

Volume 2 Issue 4, December 2002
Volume 2 Issue 3, September 2002
Volume 2 Issue 2, June 2002
Volume 2 Issue 1, March 2002

Volume 1 Issue 4, December 2001
Volume 1 Issue 3es, Fall 2001
Volume 1 Issue 2es, Summer 2001
Volume 1 Issue 1es, March 2001
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