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The Nifty Assignments project gathers great CS assignments to make their ideas and materials freely available for the CSEd community. Do you have a great assignment you would like to share with other educators? We’d love to have you apply to Nifty Assignments!

Authors submitting work to SIGCSE TS 2023 are responsible for complying with all applicable conference authorship policies and those articulated by ACM. If you have questions about any of these policies, please contact program@sigcse2023.org for clarification prior to submission.

Presentation Modality

All nifty assignments at SIGCSE TS 2023 will be available for hybrid presentation modality. A hybrid session is a live event where in-person and online attendees can interact. Presenters and attendees in hybrid sessions may be either in-person in Toronto or online. Nifty Assignment proposals need not explicitly designate online or in-person presentation, but conference organizers will need this information shortly after notification of acceptance.

Plenary
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Sat 18 Mar

Displayed time zone: Eastern Time (US & Canada) change

08:00 - 16:00
Quiet RoomLogistics / Demos / Keynotes at 810
08:30 - 09:45
Nifty AssignmentsNifty Assignments at 718A
Chair(s): Nick Parlante Stanford University, Dave Reed Creighton University, Julie Zelenski Stanford University
08:30
12m
Talk
Islands of HexHybridK12Global
Nifty Assignments
Andrew Godbout University of Prince Edward Island
DOI
08:42
12m
Talk
Mozart Musical Dice GameHybridK12
Nifty Assignments
Kevin Wayne Princeton University
DOI
08:55
12m
Talk
Nifty Assignments: Enigma Machine SimulatorHybridK12
Nifty Assignments
Eric Roberts Willamette University, Jed Rembold Willamette University
DOI
09:07
12m
Talk
Nifty Assignments - Optical Illusions Using Loops and Nested LoopsHybridK12
Nifty Assignments
Faan Tone Liu University of Denver
DOI
09:20
12m
Talk
Project: Fatal Police ShootingsHybridK12
Nifty Assignments
Melissa Lynn Gustavus Adolphus College
DOI
09:32
12m
Talk
Rising Tides: A Literal Flood-FillHybridK12
Nifty Assignments
Keith Schwarz Stanford University
DOI
08:30 - 10:30
Exhibit Hall OpenLogistics / Demos / Keynotes at Exhibit Hall G

Deadlines and Submission

Nifty Assignment submissions consist of a 1-page description outlining a common set of metadata information about the assignment, including a 250-word abstract. In addition, authors will upload a zip file containing materials from the assignment such as assignment handouts, sample data files, starter and support code files, model grading rubrics, and runnable demo application.

Nifty Assignment submissions to the SIGCSE TS 2023 must be made through EasyChair no later than Friday, October 14, 2022. The track chairs reserve the right to desk reject submissions that are incomplete after the deadline has passed.

Important Dates

Due Date Friday, October 14, 2022
Due Time 23:59 AoE (Anywhere on Earth, UTC-12h)
Submission Limits 1 page
Notification to Authors (tentative) Monday, November 14, 2022
Submission Link https://easychair.org/conferences/?conf=sigcsets2023

Abstracts

All Nifty Assignment submissions must have a plain-text abstract of up to 250 words. Abstracts should not contain subheadings or citations. The abstract should be submitted in EasyChair along with the submission metadata, and it should be included in the PDF version of the submission at the appropriate location.

Submission Templates

SIGCSE TS 2023 is not participating in the new ACM workflow, template, and production system. All Nifty submissions must be in English and formatted using the 2-column ACM SIG Conference Proceedings format and US letter size pages (8.5x11 inch or 215.9 x 279.4mm).

Page Limits: Nifty Assignment submissions are limited to a maximum of 1 page of body content (including all titles, author information, abstract, main text, tables and illustrations, acknowledgements, and supplemental material).

MS Word Authors: Please use the interim Word template provided by ACM. NOTE: For anonymized submissions, space should be reserved so that each author can be defined separately for accurate metadata identification. Multiple authors may share one affiliation. Include space for authors’ e-mail addresses whenever possible on separate lines. Grouping authors’ names or e-mail addresses, or providing an ‘e-mail alias’ is not acceptable, e.g., {anon1,anon2,anon3}@university.edu or firstname.lastname@college.org

LaTeX Authors:

At the time of submission all entries should include space for all author information, an abstract, body content, and references. NOTE: Nifty Assignment submissions may omit the following sections from the standard ACM template: keywords, CCS Concepts, and placeholders for the ACM Reference Format and copyright blocks.

Submissions that do not adhere to page limits or formatting requirements will be desk rejected without review.

Additional Format Instructions

Authors of Nifty Assignment proposals should be include information in their 1-page description that addresses question like:

  • What is so great about this assignment?
  • What niche/student is it suited for (CS1, CS2, advanced, easy, …)?
  • What does it teach?
  • How hard is it?
  • How long does it take?
  • What does it depend on?
  • What are its strengths and weaknesses?
  • Are there any lessons on assignment craft in general that can be drawn from the assignment?

The main body of the descriptions should contain the required sections in the table below, to help reviewers consider the strengths and weaknesses of the assignment.

Required Section What to Write About
Abstract A 250-word description of this assignment, its intended population, what computing concept it teaches, what it involves, and what makes it unique. If accepted, this text will be included in the SIGCSE TS proceedings.
Topics A brief discussion of the concepts, topics, and/or learning outcomes addressed by this assignment.
Audience A statement about the intended audience for this assignment. Be sure to include relevant information about the level of student (e.g., high school, 1st year undergraduate, etc) and the course (e.g., CS1, Operating Systems).
Difficulty Describe the expected difficulty and/or typical workload of this assignment for students.
Strengths What are the particular strengths of this assignment based on your experience using it? Include formative or summative observations and evidence if available.
Weaknesses What limitations, weaknesses, or potential pitfalls have you observed using this assignment with your students should other instructors wish to adopt it?
Dependencies Describe any prerequisite knowledge students need in order to approach this assignment. Also include information about technical requirements or dependencies to make this assignment work.
Variants Describe possible variations or adaptations of this assignment.

Assignment Zip File

In addition to the 1-page description, Nifty Assignment proposals must submit a zip archive containing a folder of assignment materials. Gather the materials from your assignment. Both student-facing and instructor-use materials may be appropriate. For example:

  • The assignment handout given to students (PDF or HTML)
  • Sample data files
  • Starter and support code files
  • Autograder tools and/or model grading rubric
  • Runnable demo application

Organize your submission in a directory with your name and the name of the assignment (e.g. “parlante-namesurfer”) and your web page as the index.html. Add supporting materials to the directory and link them from your index: handouts, sample application, etc. Please use relative links, so we can move the folder around and it all still works. It is not required that your folder be in final form to apply. The reviewers are evaluating the quality of the assignment itself and its applicability to the SIGCSE community, not the details of the presentation at this stage.

Accessibility: SIGCSE TS 2023 authors are strongly encouraged to prepare submissions using these templates in such a manner that the content is widely accessible to potential reviewers, track chairs, and readers. Please see these resources for preparing an accessible submission.

Double Anonymized Review

Authors must submit ONLY an anonymized version of the submission. The goal of the anonymized version is to, as much as possible, provide the author(s) of the submission with an unbiased review. The anonymized version should have ALL mentions of the authors removed (including author’s names and affiliation plus identifying information within the body of the submission such as websites or related publications). However, authors are reminded to leave sufficient space in the submitted manuscripts to accommodate author information either at the beginning or end of the submission.  LaTeX/Overleaf users are welcome to use the anonymous option, but are reminded that sufficient room must exist in the submission to include all author blocks when that option is removed.  Authors may choose to use placeholder text in the author information block, but we encourage authors to use obviously anonymized placeholders like “Author 1”, “Affiliation 1”, etc. 

Self-citations need not be removed if they are worded so that the reviewer doesn’t know if the writer is citing themselves. That is, instead of writing “We reported on our first experiment in 2017 in a previous paper [1]”, the writer might write “In 2017, an initial experiment was done in this area as reported in [1].

Submissions to the Nifty Assignments track are reviewed with the dual-anonymous review process.  The  reviewers are unaware of the author identities, and reviewers are anonymous to each other and to the authors.

The reviewing process includes a discussion phase after initial reviews have been posted. During this time, the reviewers can examine all reviews and privately discuss the strengths and weaknesses of the work in an anonymous manner through EasyChair. This discussion information can be used by the track chairs in addition to the content of the review in making final acceptance decisions.

The SIGCSE TS 2023 review process does not have a rebuttal period for authors to respond to comments, and all acceptance decisions are final.

ACM Policies

By submitting your article to an ACM Publication, you are hereby acknowledging that you and your co-authors are subject to all ACM Publications Policies, including ACM’s new Publications Policy on Research Involving Human Participants and Subjects (https://www.acm.org/publications/policies/research-involving-human-participants-and-subjects). Alleged violations of this policy or any ACM Publications Policy will be investigated by ACM and may result in a full retraction of your paper, in addition to other potential penalties, as per ACM Publications Policy.

Please ensure that you and your co-authors obtain an ORCID ID (https://orcid.org/register), so you can complete the publishing process for your accepted paper. ACM has been involved in ORCID from the start and we have recently made a commitment to collect ORCID IDs from all of our published authors (https://authors.acm.org/author-resources/orcid-faqs). The collection process has started and will roll out as a requirement throughout 2022. We are committed to improve author discoverability, ensure proper attribution and contribute to ongoing community efforts around name normalization; your ORCID ID will help in these efforts.

What Gets Published?

The full text of accepted Nifty Assignment submissions will not appear in the ACM digital library. Only the title, author metadata, and the 250-word abstract will be included in the official conference proceedings.

Presentation Details

By SIGCSE policy, at least one author of an accepted Nifty Assignment is required to register, attend, and present the work. SIGCSE TS 2023 will allow for authors to present their Nifty Assignment either in-person or online.

Further details about post-acceptance processes and presentation logistics will be provided by the time acceptance decisions are sent out.

You can view examples from past Nifty Assignments on the Nifty Assignments archive. Note that the archive versions are not formatted as submission PDFs.

Language Editing Assistance

ACM has partnered with International Science Editing (ISE) to provide language editing services to ACM authors. ISE offers a comprehensive range of services for authors including standard and premium English language editing, as well as illustration and translation services. Editing services are at author expense and do not guarantee publication of a manuscript.

Review Timeline

Reviewing PhaseStart DateEnd Date
ReviewingSaturday, October 15, 2022Sunday, October 30, 2022
Discussion & Recommendations   Monday, October 31, 2022   Friday, November 4, 2022

Overview

The Nifty Assignments project gathers great CS assignments to make their ideas and materials freely available for the CSE community. Thanks for thinking about reviewing for Nifty. To review for Nifty Assignments, you need to read and evaluate 5 submissions. Each submission is an assignment along with all its materials.

Dual-Anonymous Review Process

Authors must submit ONLY an anonymized version of the submission. The goal of the anonymized version is to, as much as possible, provide the author(s) of the submission with an unbiased review. The anonymized version should have ALL mentions of the authors removed (including author’s names and affiliation plus identifying information within the body of the submission such as websites or related publications). However, authors are reminded to leave sufficient space in the submitted manuscripts to accommodate author information either at the beginning or end of the submission. LaTeX/Overleaf users are welcome to use the anonymous option, but are reminded that sufficient room must exist in the submission to include all author blocks when that option is removed. Authors may choose to use placeholder text in the author information block, but we encourage authors to use obviously anonymized placeholders like “Author 1”, “Affiliation 1”, etc.

Self-citations need not be removed if they are worded so that the reviewer doesn’t know if the writer is citing themselves. That is, instead of writing “We reported on our first experiment in 2017 in a previous paper [1]”, the writer might write “In 2017, an initial experiment was done in this area as reported in [1].

Submissions to the Nifty Assignments track are reviewed with the dual-anonymous review process. The reviewers are unaware of the author identities, and reviewers are anonymous to each other and to the authors.

The reviewing process includes a discussion phase after initial reviews have been posted. During this time, the reviewers can examine all reviews and privately discuss the strengths and weaknesses of the work in an anonymous manner through EasyChair. This discussion information can be used by the track chairs in addition to the content of the review in making final acceptance decisions.

The SIGCSE TS 2023 review process does not have a rebuttal period for authors to respond to comments, and all acceptance decisions are final.

EasyChair Reviewer Profile

When you receive your invitation to review for SIGCSE TS 2023, please take a few moments to update your profile and select 3-5 topics that you are most qualified for reviewing. To do so, select SIGCSE TS 2023 > My topics from the menu.

Please check at most 5 topics! More topics will make it harder for the EasyChair system to make a good set of matches.

Getting Started Reviewing

Before starting your review, you may be asked by the Track Chairs to declare conflicts with any submitting authors. Please do so in a timely manner so we can avoid conflicts during assignment.

As a Reviewer, we ask that you carefully read each submission assigned to you and write a constructive review that concisely summarizes what you believe the submission to be about. When reviewing a submission, consider:

  • the strengths and weaknesses,
  • the contribution to an outstanding SIGCSE TS 2023 program and experience for attendees, and
  • how it brings new ideas or extends current ideas through replication to the field and to practitioners and researchers of computing education.

Nifty Review Guidelines

As a Reviewer, we ask that you carefully read each submission assigned to you and write a constructive review that concisely summarizes the assignment and its fit as a Nifty Assignment. When reviewing a submission, consider:

  • Is this a great assignment?
  • Does it teach topics of interest to many?
  • Are the materials high quality and adoptable by others?
  • Is it different from assignments that have already been published by Nifty Assignments?

While your review text should clearly support your scores and recommendation, please do not include your preference for acceptance or rejection of a submission in the feedback to the authors. Instead, use the provided radio buttons to make a recommendation (the authors will not see this) based on your summary review and provide any details that refer to your recommendation directly in the confidential comments to the APC or track chairs. Remember that as a reviewer, you will only see a small portion of the submissions, so one that you recommend for acceptance may be rejected when considering the other reviewer recommendations and the full set of submissions.

Discussion

The discussion and recommendation period provides the opportunity for the Track Chairs to discuss reviews and feedback so they can provide the best recommendation for acceptance or rejection to the Program Chairs and that the submission is given full consideration in the review process. We ask that Reviewers engage in discussion when prompted by other reviewers, the Track Chairs by using the Comments feature of EasyChair. During this period you will be able to revise your review based on the discussion, but you are not required to do so. The Track Chairs will make a final recommendation to the Program Chairs from your feedback.

Recalcitrant Reviewers

Reviewers who don’t submit reviews, have reviews with limited constructive feedback, or who submit inappropriate reviews will be removed from the reviewer list (as per SIGCSE policy). Recalcitrant reviewers will be informed of their removal from the reviewer list. Reviewers with repeated offenses (two within a three year period) will be removed from SIGCSE reviewing for three years.

Questions? Use the SIGCSE TS Nifty Assignments contact form.