Papers

• Organizing in the Digital Age: Understanding Community, Challenges, and Consequences in Digitally-facilitated Labor Organizing
  Frederick Reiber, Alishah Chator, Dana Calacci, Allison McDonald
  (In submission)
   
• Designing for the class struggle: Class antagonisms, societal change, and liberatory technological design
  Gina Kim, Nathan Kim, Shreya Chowdhary, Frederick Reiber, Matthew Bui
  (In submission)
   
• Construction and Preliminary Validation of a Dynamic Programming Concept Inventory
  Matthew Ferland, Varun Nagaraj Rao, Arushi Arora, Drew van der Poel, Michael Luu, Randy Huynh, Freddy Reiber, Sandra Ossman, Seth Poulsen, Michael Shindler
  arXiv link (CIGSE-2025)
  
  Concept inventories are standardized assessments that evaluate student understanding of key concepts within academic disciplines. While prevalent across STEM fields, their development lags for advanced computer science topics like dynamic programming (DP) -- an algorithmic technique that poses significant conceptual challenges for undergraduates. To fill this gap, we developed and validated a Dynamic Programming Concept Inventory (DPCI). We detail the iterative process used to formulate multiple-choice questions targeting known student misconceptions about DP concepts identified through prior research studies. We discuss key decisions, tradeoffs, and challenges faced in crafting probing questions to subtly reveal these conceptual misunderstandings. We conducted a preliminary psychometric validation by administering the DPCI to 172 undergraduate CS students finding our questions to be of appropriate difficulty and effectively discriminating between differing levels of student understanding. Taken together, our validated DPCI will enable instructors to accurately assess student mastery of DP. Moreover, our approach for devising a concept inventory for an advanced theoretical computer science concept can guide future efforts to create assessments for other under-evaluated areas currently lacking coverage.
   
• What is an Algorithms Course? Survey Results of Introductory
  Undergraduate Algorithms Courses in the U.S.
  Michael Luu, Matthew Ferland, Varun Nagaraj Rao, Arushi Arora, Randy Huynh, Frederick Reiber, Jennifer Wong-Ma, Michael Shindler
  ACM-Library Link (CIGSE-2023)
  
  Algorithms courses are a core part of many CS programs, but have received little focus in computing education, lacking statistical data about how they are generally taught. To remedy this, we present the results of the first large-scale comprehensive survey of undergraduate introductory algorithms courses at four-year institutions in the United States. Questions in the survey targeted instructor information, course concepts, the ways students are evaluated, challenges instructors encountered, and instructor envisioned improvements. We received 87 responses from 34 different states, across a wide variety of 4-year institutions. The results indicate that algorithms courses vary dramatically in most surveyed areas.
   
• Student Misconceptions of Dynamic Programming: A Replication
  Study
  Michael Shindler, Natalia Pinpin, Mia Markovic, Frederick Reiber, Jee Hoon Kim, Giles Pierre Nunez Carlos, Mine Dogucu, Mark Hong, Michael Luu, Brian Anderson, Aaron Cote, Matthew Ferland, Palak Jain, Tyler LaBonte, Leena Mathur, Ryan Moreno, Ryan Sakuma
  Official Link (CS-Education, 2022)

  Background and Context:
  We replicated and expanded on previous work about how well students learn dynamic programming, a difficult topic for students in algorithms class. Their study interviewed a number of students at one university in a single term. We recruited a larger sample size of students, over several terms, in both large public and private universities as well as liberal arts colleges.
  Objective:
  Our aim was to investigate whether the results of the previous work generalized to other universities and also to larger groups of students.
  Method:
  We interviewed students who completed the relevant portions of their algorithms class, asking them to solve problems. We observed the students' problem solving process to glean insight into how students tackle these problems.
  Findings:
  We found that students generally struggle in three ways, “technique selection,” ”recurrence building,” and “inefficient implementations.” We then explored these themes and specific misconceptions qualitatively. We observed that the misconceptions found by the previous work generalized to the larger sample of students.
  Implications:
  Our findings demonstrate areas in which students struggle, paving way for better algorithms education by means of identifying areas of common weakness to draw the focus of instructors.

• The Crew: The Quest for Planet Nine is NP-complete
  Frederick Reiber
  arXiv preprint arXiv:2110.11758 (2021)
  
  In this paper, we study the cooperative card game, The Crew: The Quest for Planet Nine from the viewpoint of algorithmic combinatorial game theory. The Crew: The Quest for Planet Nine, is a game based on traditional trick-taking card games, like bridge or hearts. In The Crew, players are dealt a hand of cards, with cards being from one of $c$ colors and having a value between 1 to $n$. Players also draft objectives, which correspond to a card in the current game that they must collect in order to win. Players then take turns each playing one card in a trick, with the player who played the highest value card taking the trick and all cards played in it. If all players complete all of their objectives, the players win. The game also forces players to not talk about the cards in their hand and has a number of "Task Tokens" which can modify the rules slightly. In this work, we introduce and formally define a perfect-information model of this problem, and show that the general unbounded version is computationally intractable. However, we also show that three bounded versions of this decision problem - deciding whether or not all players can complete their objectives - can be solved in polynomial time.


• Major Developments in the Evolution of Tabletop Game Design
  Frederick Reiber
  2021 IEEE Conference on Games (CoG) 
  Preprint
  
  Tabletop game design is very much an incremental art. Designers build upon the ideas of previous games, often improving and combining already defined game mechanics. In this work, we look at a collection of the most impactful tabletop game designs, or games that have caused a significant shift in the tabletop game design space. This work seeks to record those shifts, and does so with the aid of empirical analysis. For each game, a brief description of the game’s history and mechanics is given, followed by a discussion on its impact within tabletop game design. 

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