Physical Sciences and Mathematics Commons^™

Extreme Ungrading: Rewilding The Classroom Through Human-Centered Design, Johanna Brewer

Computer Science: Faculty Publications

Assessment in computer science education has grown reliant on rigid rubrics and intensive exams, a practice that yields capable yet compliant coders. In this article, I explore how we might use human-centered design to reexamine contemporary pedagogy and redesign our classrooms to cultivate a different type of programmer, one with a more critically engaged eye. Inspired by the ethos of agile development, I offer an alternative evaluation paradigm: Extreme Ungrading. Exploring results of a two-year case study applying this method to a software engineering class, this article distills actionable guidelines for enhancing learning outcomes through inclusive course development, and seeks …

Humans Against Large Language Models On Hard Paraphrase Detection Tasks, Jamie C. Macbeth, Ella Chang, Jingyu Gin Chen, Yining Hua, Sandra Grandic, Winnie X. Zheng

Computer Science: Faculty Publications

The ability to recognize that pairs or sets of language expressions “mean the same thing” is a cognitive task for which meaning representation is clearly a central issue. This paper uses the task of paraphrasing to study meaning representation in a cognitive system. The main claim is that a consequential part of the meaning representation for a natural language expression is a set of language-free structures that are not part of the expression in question. To support this claim, we construct a corpus of paraphrase pairs using a system that has a non-linguistic meaning represen- tation decoupled from the linguistic …

Big Ideas In Sports Analytics And Statistical Tools For Their Investigation, Benjamin S. Baumer, Gregory J. Matthews, Quang Nguyen

Statistical and Data Sciences: Faculty Publications

Sports analytics—broadly defined as the pursuit of improvement in athletic performance through the analysis of data—has expanded its footprint both in the professional sports industry and in academia over the past 30 years. In this article, we connect four big ideas that are common across multiple sports: the expected value of a game state, win probability, measures of team strength, and the use of sports betting market data. For each, we explore both the shared similarities and individual idiosyncracies of analytical approaches in each sport. While our focus is on the concepts underlying each type of analysis, any implementation necessarily …

Repytah: An Open-Source Python Package For Building Aligned Hierarchies For Sequential Data, Chenhui Jia, Lizette Carpenter, Thu Tran, Amanda Y. Liu, Sasha Yeutseyva, Mariun Tapal, Yingke Wang, Zoie Kexin Zhou, Jordan Moody, Denise Nava, Eleanor Donaher, Lillian Yusha Jiang, Ben Bruncati, Katherine M. Kinnaird

Computer Science: Faculty Publications

We introduce repytah, a Python package that constructs the aligned hierarchies representation that contains all possible structure-based hierarchical decompositions for a finite length piece of sequential data aligned on a common time axis. In particular, this representation–introduced by Kinnaird (2016) with music-based data (like musical recordings or scores) as the primary motivation–is intended for sequential data where repetitions have particular meaning (such as a verse, chorus, motif, or theme). Although the original motivation for the aligned hierarchies representation was finding structure for music-based data streams, there is nothing inherent in the construction of these representations that limits repytah to only …

Data Science Transfer Pathways From Associate's To Bachelor's Programs, Benjamin S. Baumer, Nicholas J. Horton

Statistical and Data Sciences: Faculty Publications

A substantial fraction of students who complete their college education at a public university in the United States begin their journey at one of the 935 public 2-year colleges. While the number of 4-year colleges offering bachelor’s degrees in data science continues to increase, data science instruction at many 2-year colleges lags behind. A major impediment is the relative paucity of introductory data science courses that serve multiple student audiences and can easily transfer. In addition, the lack of predefined transfer pathways (or articulation agreements) for data science creates a growing disconnect that leaves students who want to study data …

Visualizations For User-Supported State Space Exploration Of Requirements Models, Yesugen Baatartogtokh, Irene Foster, Alicia M. Grubb

Computer Science: Faculty Publications

Automated analysis has been used in goal-oriented requirements engineering (GORE) to evaluate scenarios and make trade-off decisions. For higher complexity problems (e.g., backwards analysis), using a search-based solver may be more efficient than custom algorithms. When these black-box solvers produce a single solution, users may be suspicious about whether the given answer is ideal or believable. Users would like to explore the potential solutions but are prevented from doing so because these inquiries often suffer from a state explosion problem. In this RE@Next! paper, we introduce the use of valuation-based filtering and coloring to assist users in understanding a solution …

Bringing Stakeholders Along For The Ride: Towards Supporting Intentional Decisions In Software Evolution: Supplemental Material, Alicia M. Grubb, Paola Spoletini

Data

Supplemental material for the research paper entitled, "Bringing Stakeholders Along for the Ride: Towards Supporting Intentional Decisions in Software Evolution". This paper presents an initial literature review to define intentionality, disambiguate it from its use in literature, and position it in relation to similar concepts. This supplement contains the literature review data file.

Evaluation Of Edison's Data Science Competency Framework Through A Comparative Literature Analysis, Karl R. B. Schmitt, Linda Clark, Katherine M. Kinnaird, Ruth E. H. Wertz, Björn Sandstede

Statistical and Data Sciences: Faculty Publications

During the emergence of Data Science as a distinct discipline, discussions of what exactly constitutes Data Science have been a source of contention, with no clear resolution. These disagreements have been exacerbated by the lack of a clear single disciplinary 'parent.' Many early efforts at defining curricula and courses exist, with the EDISON Project's Data Science Framework (EDISON-DSF) from the European Union being the most complete. The EDISON-DSF includes both a Data Science Body of Knowledge (DS-BoK) and Competency Framework (CF-DS). This paper takes a critical look at how EDISON's CF-DS compares to recent work and other published curricular or …

An Experiment On The Effects Of Using Color To Visualize Requirements Analysis Tasks: Supplemental Material, Yesugen Baatartogtokh, Irene Foster, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the paper: "An Experiment on the Effects of using Color to Visualize Requirements Analysis Tasks".
This paper is a scientific evaluation of the effectiveness and usability of EVO. We conduct an experiment to measure any effect of using colors to represent evidence pairs.

Visualizations For User-Supported State Space Exploration Of Goal Models: Supplemental Material, Yesugen Baatartogtokh, Irene Foster, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the research paper entitled, "Visualizations for User-supported State Space Exploration of Goal Models". This paper presents a technique for valuation-based filtering and coloring to assist users in understanding a solution space and selecting custom states from it. This supplement contains the data from our initial evaluation and associated models.

An Experiment On The Effects Of Using Color To Visualize Requirements Analysis Tasks, Yesugen Baatartogtokh, Irene Foster, Alicia M. Grubb

Computer Science: Faculty Publications

Recent approaches have investigated assisting users in making early trade-off decisions when the future evolution of project elements is uncertain. These approaches have demon-strated promise in their analytical capabilities; yet, stakeholders have expressed concerns about the readability of the models and resulting analysis, which builds upon Tropos. Tropos is based on formal semantics enabling automated analysis; however, this creates a problem of interpreting evidence pairs. The aim of our broader research project is to improve the process of model comprehension and decision making by improving how analysts interpret and make decisions. We extend and evaluate a prior approach, called EVO, …

Coming Out While Going Fast: Queer Conviviality In Speedrunning Live Streams, Johanna Brewer

Computer Science: Faculty Publications

Drawing on ethnographic research of LGBTQIA+ live streaming speedrunners, this article demonstrates how by centering queer perspectives, we can catalyze meaningful social changes for all. Though for most people, beating the original Super Mario Bros. in under five minutes would seem unfathomably difficult, LGBTQIA+ speedrunning live streamers regularly accomplish this superhuman feat, while coming out to an audience of thousands at the same time. For queer and trans folks, broadcasting such a transgressive, transformational form of play is defiant demonstration of vulnerability; one that creates a comfortable space for a community to thrive, by cultivating a culture of queer conviviality. …

Image Schema Decompositions Of The Conceptual Dependency Ingest Primitive: A Study Of Paraphrases, Jamie C. Macbeth, Alexis Kilayko, Zoie Zhao, Sophie Song, Winniw X. Zheng

Computer Science: Faculty Publications

One of the hallmarks of the Schank-Minsky Conceptual Dependency Trans-Frames meaning representation system is that it attempts to express complex meanings by building large and complex conceptual structures using a relatively small number of primitives. Recently comparisons of image schemas with Conceptual Dependency primitives revealed ways of possibly reducing the number of primitives while maintaining the expressiveness of the set—an important research goal because it increases the flexibility and richness of the primitive-decomposed structures in a way that better approximates human cognition. Inspired by this prior work, we employ a paraphrase generation system to explore the replacement of the Conceptual …

A Proposal For Primitive Decomposition Of Spatial Orientation Relationships, Jamie C. Macbeth, Mackie Zhou, Zoie Zhao

Computer Science: Faculty Publications

This short paper continues work on primitive decomposition systems for meaning representation which combine image schemas and conceptual dependency primitive systems. An important thread of this research seeks small abstract sets of conceptual primitives so that decompositions of imagery evoked by language give rise to rich sets of mappings between language and the language-free representations, reflecting the linguistic variation of human language behavior. In this brief paper, we present a proposal for novel primitive decompositions of positions, spatial relationships, and orientations of objects in space in a conceptual representation framework. As an abstract first approximation, we introduce a spatial primitive …

More Human Than Human: Llm-Generated Narratives Outperform Human-Llm Interleaved Narratives, Zoie Zhao, Sophie Song, Bridget Duah, Jamie C. Macbeth, Scott Carter, Monica Van, Nayeli Bravo, Matthew Klenk, Katherine Sieck, Alexandre Filipowicz

Computer Science: Faculty Publications

Narrative story generation has gained emerging interest in the field of large language models. The present paper aims to compare stories generated by an LLM only (non-interleaved) with those generated by interleaving human-generated and LLM-generated text (interleaved). The study’s hypothesis is that interleaved stories would perform better than non-interleaved stories. To verify this hypothesis, we conducted two tests with roughly 500 participants each. Participants were asked to rate stories of each type, including an overall score or preference and four facets—logical soundness, plausibility, understandability, and novelty. Our findings indicate that interleaved stories were in fact less preferred than non-interleaved stories. …

Playing Unbound: Towards A Radically Intersectional Hci, Johanna Brewer

Computer Science: Faculty Publications

This short essay is a call to action for digital games researchers to positively transform the future of HCI by meaningfully adopting an explicitly intersectional approach to our work as a scholarly community.

Proceedings Of The Tenth Annual Conference On Advances In Cognitive Systems, Jamie C. Macbeth, Leilani Gilpin, Michael T. Cox

Computer Science: Faculty Publications

We hope you will enjoy these proceedings of the Tenth Annual Conference on Advances in Cognitive Systems (ACS). The event was the first hybrid meeting of ACS in is history. It took place virtually via Zoom and physically at George Mason University in Arlington, Virginia, from Saturday, November 19, to Tuesday, November 22, 2022. We are so delighted to be part of continuing this important venue that focuses on the original long-standing goals and challenges of artificial intelligence research. The conference program consisted of 37 papers consisting of ten 30-minute long talks, fifteen 20-minute short talks, twelve posters, three invited …

Implementing Github Actions Continuous Integration To Reduce Error Rates In Ecological Data Collection, Albert Y. Kim, Valentine Herrmann, Ross Barreto, Brianna Calkins, Erika Gonzalez-Akre, Daniel J. Johnson, Jennifer A. Jordan, Lukas Magee, Ian R. Mcgregor, Nicolle Montero, Karl Novak, Teagan Rogers, Jessica Shue, Kristina J. Anderson-Teixeira

Statistical and Data Sciences: Faculty Publications

Accurate field data are essential to understanding ecological systems and forecasting their responses to global change. Yet, data collection errors are common, and data analysis often lags far enough behind its collection that many errors can no longer be corrected, nor can anomalous observations be revisited. Needed is a system in which data quality assurance and control (QA/QC), along with the production of basic data summaries, can be automated immediately following data collection.

Here, we implement and test a system to satisfy these needs. For two annual tree mortality censuses and a dendrometer band survey at two forest research sites, …

Digital Intimacy In Real Time: Live Streaming Gender And Sexuality, Bo Ruberg, Johanna Brewer

Computer Science: Faculty Publications

This article serves as the guest editors’ introduction to the Television and New Media special issue dedicated to gender and sexuality in live streaming. Live streaming is a key part of the contemporary digital media landscape; it sits at the center of wide-reaching shifts in how culture, entertainment, and labor are expressed and experienced online today. Gender and sexuality are crucial elements of live streaming. Across live streaming’s many forms, these elements manifest in myriad ways: from gendered performances to gender-based harassment, from LGBTQ community building to real-time sex work. This special issue models an interdisciplinary approach to studying gender …

A Systematic Literature Review Of Requirements Engineering Education, Marian Daun, Alicia M. Grubb, Viktoria Stenkova, Bastian Tenbergen

Computer Science: Faculty Publications

Requirements engineering (RE) has established itself as a core software engineering discipline. It is well acknowledged that good RE leads to higher quality software and considerably reduces the risk of failure or budget-overspending of software development projects. It is of vital importance to train future software engineers in RE and educate future requirements engineers to adequately manage requirements in various projects. To this date, there exists no central concept of what RE education shall comprise. To lay a foundation, we report on a systematic literature review of the feld and provide a systematic map describing the current state of RE …

Auxetic Interval Determination And Experimental Validation For A Three-Dimensional Periodic Framework, Ciprian S. Borcea, Freek G.J. Broeren, Just L. Herder, Ileana Streinu, Volkert Van Der Wijk

Computer Science: Faculty Publications

Auxetic behavior refers to lateral widening upon stretching or, in reverse, lateral shrinking upon compression. When an initially auxetic structure is actuated by compression or extension, it will not necessarily remain auxetic for larger deformations. In this paper, we investigate the auxetic range in the deformation of a periodic framework with one degree of freedom. We use geometric criteria to identify the interval where the deformation is auxetic and validate these theoretical findings with compression experiments on sample structures with (Formula presented.) unit cells.

An Educator’S Perspective Of The Tidyverse, Mine Çetinkaya-Rundel, Johanna Hardin, Benjamin Baumer, Amelia Mcnamara, Nicholas J. Horton, Colin W. Rundel

Statistical and Data Sciences: Faculty Publications

Computing makes up a large and growing component of data science and statistics courses. Many of those courses, especially when taught by faculty who are statisticians by training, teach R as the programming language. A number of instructors have opted to build much of their teaching around use of the tidyverse. The tidyverse, in the words of its developers, “is a collection of R packages that share a high-level design philosophy and low-level grammar and data structures, so that learning one package makes it easier to learn the next” (Wickham et al. 2019). These shared principles have led to the …

Comparison Of Caregiver- And Child-Reported Quality Of Life In Children With Sleep-Disordered Breathing, Phoebe Kuo Yu, Kaitlyn Cook, Jiayan Liu, Raouf S. Amin, Craig Derkay, Lisa M. Elden, Susan L. Garetz, Alisha S. George, Sally Ibrahim, Stacey L. Ishman, Erin M. Kirkham, S. Kamal Naqvi, Jerilynn Radcliffe, Kristie R. Ross, Gopi B. Shah, Ignacio E. Tapia, H. Gerry Taylor, David A. Zopf, Susan Redline, Cristina M. Baldassari

Statistical and Data Sciences: Faculty Publications

Objective. Caregivers frequently report poor quality of life(QOL) in children with sleep-disordered breathing (SDB).Our objective is to assess the correlation between care-giver- and child-reported QOL in children with mild SDBand identify factors associated with differences between caregiver and child report.

Study Design. Analysis of baseline data from a multi-institutional randomized trialSetting. Pediatric Adenotonsillectomy Trial for Snoring, where children with mild SDB (obstructive apnea-hypopnea index\3) were randomized to observation or adenotonsillectomy.

Methods. The Pediatric Quality of Life Inventory (Peds QL)assessed baseline global QOL in participating children 5 to12 years old and their caregivers. Caregiver and child scores were compared. Multivariable regression …

A Divide & Concur Approach To Collaborative Goal Modeling With Merge In Early-Re: Supplemental Material, Kathleen R. Hablutzel, Anisha Jain, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the paper:
"A Divide & Concur Approach to Collaborative Goal Modeling with Merge in Early-RE"
This paper proposes a formal approach to the problem of merging the attributes of intentions and actors, once these elements have been matched.

Three Major Instructional Approaches For Requirements Engineering, Marian Daun, Alicia M. Grubb, Bastian Tenbergen

Computer Science: Faculty Publications

In this talk, we report on our findings from the paper A Survey of Instructional Approaches in the Requirements Engineering Education Literature [DGT21], which has been accepted at and published in the proceedings of the 2021 IEEE International Conference on Requirements Engineering. The paper reports the findings of a systematic literature review to define and investigate the current state of research on requirements engineering education.

Novel Primitive Decompositions For Real-World Physical Reasoning, Mackie Zhoou, Bridget Duah, Jamie C. Macbeth

Computer Science: Faculty Publications

In this work, we are concerned with developing cognitive representations that may en- hance the ability for self-supervised learning systems to learn language as part of their world explorations. We apply insights from in-depth language understanding systems to the problem, specifically representations which decompose language inputs into language-free structures that are complex combinations of primitives representing cognitive abstractions such as object permanence, movement, and spatial relationships. These decompositions, performed by a system traditionally called a conceptual analyzer, link words with complex non-linguistic structures that engender the rich relations between language expressions and world exploration that are a familiar aspect of …

Interleaving A Symbolic Story Generator With A Neural Network-Based Large Language Model, Jingwen Xiang, Zoie Zhao, Mackie Zhou, Megan Mckenzie, Alexis Kilayko, Jamie C. Macbeth, Scott Carter, Katharine Sieck, Matthew Klenk

Computer Science: Faculty Publications

Research in deep learning has recently produced models of natural language that are capable of generating natural language output which, at a glance, has strong similarities to that written by intelligent humans. However, the texts produced by deep learning-based large language models (LLMs), upon deeper examination, reveal the challenges that they have in producing outputs that maintain logical coherence. One specific application area of interest for LLMs is in fictional narrative generation, a mode of operation in which stories are generated by the model in response to a prompt text that indicates the start of a story or the desired …

Script Combination For Enhanced Story Understanding And Story Generation Systems, Megan Mckenzie, Alexis Kilayko, Jamie C. Macbeth, Scott Carter, Katharine Sieck, Matthew Klenk

Computer Science: Faculty Publications

Scripts, knowledge structures defining sequences of events in stereotypical social situations, were traditionally used to simulate the ways in which people can infer unstated details in understanding a story. In this paper, we describe the MUltiple SCRipt AcTivator (MUSCRAT), and the Script Combination Applier Mechanism (SCAM), significant enhancements of Cullingford’s Script Applier Mechanism which accomplish two novel aims. One system, MUSCRAT, is able to activate more than one script and use them during a story understanding process. The second system, SCAM, uses scripts for story generation, using script variables as “terminals” for combining two or more scripts together to create …

The Forestecology R Package For Fitting And Assessing Neighborhood Models Of The Effect Of Interspecific Competition On The Growth Of Trees, Albert Y. Kim, David N. Allen, Simon P. Couch

Statistical and Data Sciences: Faculty Publications

Neighborhood competition models are powerful tools to measure the effect of interspecific competition. Statistical methods to ease the application of these models are currently lacking. We present the forestecology package providing methods to (a) specify neighborhood competition models, (b) evaluate the effect of competitor species identity using permutation tests, and (cs) measure model performance using spatial cross-validation. Following Allen and Kim (PLoS One, 15, 2020, e0229930), we implement a Bayesian linear regression neighborhood competition model. We demonstrate the package's functionality using data from the Smithsonian Conservation Biology Institute's large forest dynamics plot, part of the ForestGEO global network of research …

Facilitating Team-Based Data Science: Lessons Learned From The Dsc-Wav Project, Chelsey Legacy, Andrew Zieffler, Benjamin S. Baumer, Valerie Barr, Nicholas J. Horton

Statistical and Data Sciences: Faculty Publications

While coursework provides undergraduate data science students with some relevant analytic skills, many are not given the rich experiences with data and computing they need to be successful in the workplace. Additionally, students often have limited exposure to team-based data science and the principles and tools of collaboration that are encountered outside of school. In this paper, we describe the DSC-WAV program, an NSF-funded data science workforce development project in which teams of undergraduate sophomores and juniors work with a local non-profit organization on a data-focused problem. To help students develop a sense of agency and improve confidence in their …