Faculty Open Access Articles

Permanent link for this collectionhttps://hdl.handle.net/2022/30149

This collection contains articles made publicly available under the IU Bloomington Faculty Open Access Policy. The IU Libraries Scholarly Communication Department facilitates the deposit of articles into this collection.

This collection also contains open access book chapters and other scholarly works authored by IU faculty.

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Now showing 1 - 20 of 2996

Exploring Educational Messages About Sexual Choking: Results of a Feasibility, Acceptability, and Efficacy Study Among College Students
(Springer Nature, 2025-11-20) Herbenick, Debby; Fu, Tsung-chieh; Simić Stanojević, Ivanka; Rosenberg, Molly; Eastman-Mueller, Heather; Patterson Perry, Callie; Kawata, Keisuke; Strack, Gael; Gwinn, Casey; Wright, Paul J
IntroductionSexual choking has become prevalent among young adults, including college students, and poses significant health risks; yet, no evidence-based interventions address it. Using data from a campus-representative survey of college students, we examined participants’ age at first learning about choking and their views about teaching youth about choking and its risks. We also randomized students to one of three groups and tested the feasibility, acceptability, and preliminary efficacy of educational messages related to choking.MethodThis study uses data from a campus-representative confidential online survey of 973 undergraduate students in Fall 2021.ResultsOn average, students had first learned about sexual choking at 15.3 years old. Also, 61.1% felt that youth should first be taught about choking and its health risks during high school, with an additional 22.1% indicating middle school. Our educational messages had high feasibility and acceptability ratings and showed strong evidence of preliminary efficacy among students who had previously choked or been choked during sexual activities.ConclusionsMost students had first learned about choking as adolescents, highlighting the need for fact-based sexuality education. We found broad student support for learning about choking and its risks from college health professionals, including faculty who teach sexuality- and health-related courses. Our educational messages can be expanded to support student health and safety.Policy ImplicationsFindings have implications for the development of educational programming to address sexual choking. Public health agencies also have an important role in education.
A Multi-View Predictive Student Modeling Framework with Interpretable Causal Graph Discovery for Collaborative Learning Analytics
(2025) Acosta, H; Lee, S; Hong, D; Min, W; Mott, B; Hmelo-Silver, C; Lester, J
Understanding the relationship between student behaviors and learning outcomes is crucial for designing effective collaborative learning environments. However, collaborative learning analytics poses significant challenges, not only due to the complex interplay between collaborative problemsolving and collaborative dialogue but also due to the need for model interpretability. To address these challenges, this paper introduces a multi-view predictive student modeling framework using causal graph discovery. We first extract interpretable behavioral features from students’ collaborative dialogue data and game trace logs to predict student learning within a collaborative game-based learning environment. We then apply constraint-based sequential pattern mining to identify cognitive and social behavioral patterns in student’s data to improve predictive power. We employ unified causal modeling for interpreting model outputs, using causal discovery methods to reveal key interactions among student behaviors that significantly contribute to predicting learning outcomes and identifying frequent collaborative problem-solving skills. Evaluations of the predictive student modeling framework show that combining features from dialogue and in-game behaviors improves the prediction of student learning gains. The findings highlight the potential of multi-view behavioral data and causal analysis to improve both the effectiveness and the interpretability of collaborative learning analytics.
Collaborative Game-based Learning Analytics: Predicting Learning Outcomes from Game-based Collaborative Problem Solving Behaviors
(Association for Computing Machinery (ACM), 2025-03-03) Acosta, Halim; Hong, Daeun; Lee, Seung; Min, Wookhee; Mott, Bradford; Hmelo-Silver, Cindy; Lester, James
Skills in collaborative problem solving (CPS) are essential for the 21st century, enabling students to solve complex problems effectively. As the demand for these skills rises, understanding their development and manifestation becomes increasingly important. To address this need, we present a data-driven framework that identifies behavioral patterns associated with CPS practices and can assess students’ learning outcomes. It provides explainable insights into the relationship between students’ behaviors and learning performance. We employ embedding and clustering techniques to categorize similar trace logs and apply Latent Dirichlet allocation to generate meaningful descriptors. To capture the temporal evolution of student behaviors, we introduce a graph-based representation of transitions between behavior patterns extracted using constraint-based pattern mining. We map behavioral patterns to a CPS ontology by analyzing how action sequences correspond to specific CPS practices. Analysis of semi-structured trace log data from 61 middle school students engaged in collaborative game-based learning reveals that the extracted behavioral patterns significantly predict student learning gains using generalized additive models. Our analysis identifies patterns that provide insights into the relationship between student use of CPS practices and learning outcomes.
Disagreeing softly: Supporting students in managing disagreement in peer critique
(Springer Nature, 2025-06-01) Zhou, Jinzhi; Hmelo-Silver, Cindy E; Ryan, Zach; Stiso, Christina; Murphy, Danielle; Danish, Joshua; Chinn, Clark A; Duncan, Ravit Golan
Disagreement is often perceived negatively, yet it can be beneficial for learning and scientific inquiry. However, students tend to avoid engaging in disagreement. Peer critique activities offer a promising way to encourage students to embrace disagreement, which supports learning as students articulate their ideas, making them available for discussion, revision, and refinement. This study aims to better understand how students express disagreement during peer critique within small groups and how that affects moving their inquiry forward. It explores 5th-grade students’ management of disagreement within a computer-supported collaborative modeling environment. Using conversation analysis, we identified various forms of disagreements employed by students when engaging with different audiences. We observed a tendency for students to disagree softly; that is, disagreement was implied and/or mitigated. Students’ resolution of both direct and soft disagreements effectively promoted their collective knowledge advancement, including building shared scientific understanding and improving their models, while maintaining a positive socio-emotional climate. These findings have implications for designing CSCL environments with respect to supporting students in providing and responding to peer critiques at the group level.
Recognizing Multi-Party Epistemic Dialogue Acts During Collaborative Game-Based Learning Using Large Language Models
(Springer Nature, 2025-06-01) Acosta, Halim; Lee, Seung; Bae, Haesol; Feng, Chen; Rowe, Jonathan; Glazewski, Krista; Hmelo-Silver, Cindy; Mott, Bradford; C. Lester, James
Understanding students’ multi-party epistemic and topic based-dialogue contributions, or how students present knowledge in group-based chat interactions during collaborative game-based learning, offers valuable insights into group dynamics and learning processes. However, manually annotating these contributions is labor-intensive and challenging. To address this, we develop an automated method for recognizing dialogue acts from text chat data of small groups of middle school students interacting in a collaborative game-based learning environment. Our approach utilizes dual contrastive learning and label-aware data augmentation to fine-tune large language models’ underlying embedding representations within a supervised learning framework for epistemic and topic-based dialogue act classification. Results show that our method achieves a performance improvement of 4% to 8% over baseline methods in two key classification scenarios. These findings highlight the potential for automated dialogue act recognition to support understanding of how meaning-making occurs by focusing on the development and evolution of knowledge in group discourse, ultimately providing teachers with actionable insights to better support student learning.
Instruction Based on Collaborative Learning
(Taylor & Francis, 2025-10-28) Hmelo-Silver, Cindy E; Zou, Xiaotian; Danish, Joshua
This chapter reviews instructional approaches to collaborative learning. It reviews key theoretical frameworks including cognitive, social cognitive, social constructivist, sociocultural, and embodied collaboration perspectives, each offering unique insights into the dynamics of collaborative learning. It also explores various research methodologies used to study collaborative learning, such as experimental designs, qualitative methods, and mixed-method approaches. Instructional approaches for enhancing collaborative learning are described, including the design of group-worthy tasks, scaffolding, and teacher facilitation. Several specific examples are described including problem-based learning and jigsaw approaches as well as discussing the role of technology in computer-supported collaborative learning. Further research needs to explore the role of advanced technologies in supporting collaborative learning. Collaborative learning stands out as a powerful pedagogical approach that fosters the collective construction of knowledge, promotes deep engagement, critical thinking, and problem-solving skills among learners.
Measuring upper-elementary students’ understanding of AI concepts – a Rasch model analysis
(Emerald, 2025-09-19) Chakraburty, Srijita; Glazewski, Krista D; Hmelo-Silver, Cindy E; Valdivia, Dubravka Svetina; Ottenbreit-Leftwich, Anne; Mott, Bradford; Lester, James
Purpose This paper aims to introduce a novel AI learning progression for upper-elementary students and aligns assessment items across levels of each construct to gather evidence of understanding. It also validates this quantitative measure by examining these items as two subscales for psychometric properties using the Rasch model. Design/methodology/approach Conducting a cognitive analysis of diverse data sources, including the AI4K12 big ideas (Touretzky et al., 2019), student performance on assessment items, and classroom activities from prior implementations of an AI curriculum intervention (Glazewski et al., 2022), and drawing insights from subject matter experts, this paper outlines the design of the learning progression. The second section delves into the refinement and mapping of assessment items and an evaluation of their psychometric properties to ensure the reliable placement of students within the progression. Findings This project identified key starting points for students and outlined how their understanding of core AI concepts should develop. The validation of the two subscales resulted in a reliable tool for accurately assessing students’ AI abilities. This tool helps educators match assessment questions to students’ current understanding and guide their progression through the learning journey. Originality/value This learning progression offers a unique framework for teaching AI to younger students, addressing a gap in K-12 education. It provides a roadmap for progressively teaching AI concepts, allowing educators to design lessons and assessments that are appropriate for students’ developmental stages.
The Intersection of Scholarly Communication and Acquisitions: Required Course Materials as E-book Purchases
(University of Michigan Library, 2025-07-30) Cooke, Rivkah; Hare, Sarah; Stoll Farrell, Karen
Librarians at Indiana University Bloomington (IUB) developed a pilot project to obtain course material data and purchase multi-user e-books for classes. This is a practice that peer libraries like Illinois State University and Virginia Commonwealth University have utilized to further course material affordability. These proceedings provide a high-level overview of how the project was implemented, with specific details about the workflow that other libraries can adapt to their context, including identifying partners, getting funding, securing and cleaning data, comparing this data to existing holdings and licenses, purchasing content, and outreach to professors. The paper also provides ideas for scaling IUB’s program down so that libraries of all sizes can create a program that is appropriate for their context. It concludes with the strengths of this model as well as the considerations that libraries should consider before creating similar programs.
Launch of the NASIG Model Digital Preservation Policy
(University of Michigan Library, 2023-11-02) Staines, Heather; Tavernier, Willa Liburd; Wickham, Abeni; Enoch, Todd
Digital preservation is a significant issue if scholarship is to remain available to future users. All organizations involved in scholarly production and dissemination have a role to play. Champions are needed to raise awareness and engage stakeholders. To help, the NASIG Digital Preservation Committee has developed a Model Digital Preservation Policy. This tool is designed to help you measure, grow, and publicize your organization’s commitment to preserving its scholarship. It includes advice on identifying and taking first steps, more advanced options and activities, and opportunities to share and refine professional experiences.
The American Petroleum Institute: Sponsored Motion Pictures in the Service of Public Relations
(2021) Waller, Gregory A.
Measurements of Total OH Reactivity During CalNex‐LA
(2021) Hansen, R. F.; Griffith, S. M.; Dusanter, S.; Gilman, J. B.; Graus, M.; Kuster, W. C.; Veres, P. R.; de Gouw, J. A.; Warneke, C.; Washenfelder, R. A.; Young, C. J.; Brown, S. S.; Alvarez, S. L.; Flynn, J. H.; Grossberg, N. E.; Lefer, B.; Rappenglueck, B.; Stevens, Philip S
Total OH reactivity was measured during the California Research at the Nexus of Air Quality and Climate Change field campaign at the Pasadena ground site using a turbulent flow tube reactor with laser-induced fluorescence detection of the OH radical. Collocated measurements of volatile organic compounds (VOCs), inorganic species, and meteorological parameters were made and used to calculate the total OH reactivity, which was then compared to the measured values. An analysis of the OH reactivity measurements finds that although the measured reactivity correlated well with the calculated reactivity, the measurements were consistently greater than the calculations for all times during the day, with an average missing OH reactivity of 8–10 s−1, accounting for approximately 40% of the measured total OH reactivity. An analysis of correlations with both anthropogenic tracers of combustion and oxygenated VOCs as well as air trajectories during the campaign suggest that the missing OH reactivity was likely due to a combination of both unmeasured local emissions and unmeasured oxidation products transported to the site. Approximately 50% of the missing OH reactivity may have been due to emissions of unmeasured volatile chemical products, such as pesticides, cleaning agents, and personal care products.
Quantifying Nitrous Acid Formation Mechanisms Using Measured Vertical Profiles During the CalNex 2010 Campaign and 1D Column Modeling
(2021) Tuite, Katie; Thomas, Jennie L.; Veres, Patrick R.; Roberts, James M.; Stevens, Philip S; Griffith, Stephen M.; Dusanter, Sebastien; Flynn, James H.; Ahmed, Shaddy; Emmons, Louisa; Kim, Si‐Wan; Washenfelder, Rebecca; Young, Cora; Tsai, Catalina; Pikelnaya, Olga; Stutz, Jochen
Nitrous acid (HONO) is an important radical precursor that can impact secondary pollutant levels, especially in urban environments. Due to uncertainties in its heterogeneous formation mechanisms, models often under predict HONO concentrations. A number of heterogeneous sources at the ground have been proposed but there is no consensus about which play a significant role in the urban boundary layer. We present a new one-dimensional chemistry and transport model which performs surface chemistry based on molecular collisions and chemical conversion, allowing us to add detailed HONO formation chemistry at the ground. We conducted model runs for the 2010 CalNex campaign, finding good agreement with observations for key species such as O3, NOx, and HOx. With the ground sources implemented, the model captures the diurnal and vertical profile of the HONO observations. Primary HOx production from HONO photolysis is 2–3 times more important than O3 or HCHO photolysis at mid-day, below 10 m. The HONO concentration, and its contribution to HOx, decreases quickly with altitude. Heterogeneous chemistry at the ground provided a HONO source of 2.5 × 1011 molecules cm−2 s−1 during the day and 5 × 1010 molecules cm−2 s−1 at night. The night time source was dominated by NO2 hydrolysis. During the day, photolysis of surface HNO3/nitrate contributed 45%–60% and photo-enhanced conversion of NO2 contributed 20%–45%. Sensitivity studies addressing the uncertainties in both photolytic mechanisms show that, while the relative contribution of either source can vary, HNO3/nitrate is required to produce a surface HONO source that is strong enough to explain observations.
The Local Spillover Effect of Corporate Accounting Misconduct: Evidence from City Crime
(2021) Holzman, Eric; Miller, Brian; Williams, Brian
This study documents a spillover effect of accounting fraud by showing that after the revelation of accounting misconduct, there is an increase in financially motivated neighborhood crime (robberies, thefts, etc.) in the cities where these misconduct firms are located. We find that more visible accounting frauds (e.g., greater media attention and larger stock price declines) are more strongly associated with a future increase in financially motivated neighborhood crime. We also find that the association between fraud revelation and increased future financially motivated crime is strongest when local job markets are shallower and where local income inequality is high, consistent with adverse shocks from fraud putting pressure on local communities. Combined, our study provides evidence that the societal ramifications of corporate accounting misconduct extend beyond adversely impacting a firm's capital providers and industry peers to negatively influence the daily life of the residents in the firm's local community.
Sensitivity of Total Column Ozone to Stratospheric Sulfur Injection Strategies
(2021) Tilmes, S.; Richter, J. H.; Kravitz, Benjamin Stephen; MacMartin, D. G.; Glanville, A. S.; Visioni, D.; Kinnison, D. E.; Müller, R.
We explore the impact of different stratospheric sulfur injection strategies to counter greenhouse gas induced warming on total column ozone (TCO), including high and low altitude injections at four latitudes, equatorial injections, and using a configuration with higher vertical resolution, based on a state-of-the-art Earth system model. The experiments maintain global surface temperatures at 2020 conditions, while following the unmitigated future scenario. Within the first 10 years of the injection, we find an abrupt deepening of the Antarctic ozone hole by 8%–20% and changes up to urn:x-wiley:00948276:media:grl63028:grl63028-math-00015% for other regions and seasons. The ozone hole recovery is delayed by ∼25 to over 55 years, with the fastest recovery for low-altitude injections and slowest for equatorial injections. Mid to high-latitude TCO increases by urn:x-wiley:00948276:media:grl63028:grl63028-math-000315% in Northern Hemisphere winter and spring between 2010–2019 and 2080–2089 due to both increasing greenhouse gases and increasing sulfur injections. Implications for ecosystems need to be investigated.
HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network Architecture
(2021) Lou, Qian; Jiang, Lei
Recently Homomorphic Encryption (HE) is used to implement Privacy-Preserving Neural Networks (PPNNs) that perform inferences directly on encrypted data without decryption. Prior PPNNs adopt mobile network architectures such as SqueezeNet for smaller computing overhead, but we find naïvely using mobile network architectures for a PPNN does not necessarily achieve shorter inference latency. Despite having less parameters, a mobile network architecture typically introduces more layers and increases the HE multiplicative depth of a PPNN, thereby prolonging its inference latency. In this paper, we propose a \textbf{HE}-friendly privacy-preserving \textbf{M}obile neural n\textbf{ET}work architecture, \textbf{HEMET}. Experimental results show that, compared to state-of-the-art (SOTA) PPNNs, HEMET reduces the inference latency by 59.3, and improves the inference accuracy by 0.4.
Does the Individual Mandate Affect Insurance Coverage? Regression Kink Evidence from the Population of Tax Returns
(2021) Lurie, Ithai Z.; Sacks, Daniel W.; Heim, Bradley
We estimate the effect of the ACA's individual mandate on insurance coverage using regression discontinuity and regression kink designs with tax return data. We have four key results. First, the actual penalty paid per uninsured month is less than half the statutory amount. Second, nonetheless, we find visually clear and statistically significant responses to both extensive margin exposure to the mandate and to marginal increases in the mandate penalty. Third, we find substantial heterogeneity in who responds; men are especially responsive. Fourth, our estimates imply fairly small quantitative responses to the individual mandate, especially in the Health Insurance Exchanges.
Observational Studies of the Effect of Medicaid on Health: Controls Are Not Enough
(2021) Freedman, Seth; Goodman-Bacon, Andrew; Hammarlund, Noah
Covariate-adjusted cross-sectional comparisons show that Medicaid patients have worse health outcomes than other patients. We evaluate the validity of this research design for estimating the causal effect of Medicaid on mortality. Even after controlling for common covariates, Medicaid patients have worse preoperative health and lower socioeconomic status than privately insured patients. Controlling for additional variables shrinks the mortality differences but still does not eliminate imbalance in other predetermined variables. These results can be explained by fairly weak assumptions about unmeasured confounders. We conclude that cross-sectional observational methods do not produce valid causal estimates of Medicaid’s mortality effects.
Applicability of a salient belief elicitation to measure abortion beliefs
(2021) Maier, Julie M.; Jozkowski, Kristen Nicole; Valdez, Danny; Crawford, Brandon Lee; Turner, Ronna C.; Lo, Wen-Juo
Objectives: Salient belief elicitations (SBEs), informed by the Reasoned Action Approach (RAA), are used to identify 3 sets of beliefs – behavioral, control, and normative – that influence attitudes toward a health behavior. SBEs ask participants about their own beliefs through open-ended questions. We adapted a SBE by focusing on abortion, which is infrequently examined through SBEs; we also included a survey version that asked participants their views on what a hypothetical woman would do if contemplating an abortion. Given these deviations from traditional SBEs, the purpose of this study was to assess if the adapted SBE was understood by participants in English and Spanish through cognitive interviewing. Methods: We examined participants' interpretations of SBE items about abortion to determine if they aligned with the corresponding RAA construct. We administered SBE surveys and conducted cognitive interviews with US adults in both English and Spanish. Results: Participants comprehended the SBE questions as intended. Participants' interpretations of most questions were also in line with the respective RAA construct. Conclusions: SBE survey questions were comprehended well by participants. We discuss areas in which SBE questions can be modified to improve alignment with the underlying RAA construct to assess abortion beliefs.
The Ecology of Exchange: The Monetization of Roman Egypt
(2021) Elliott, Colin Peter
The Egyptian experience of monetization—especially during the Roman period—subverts colonializing historiographies in which the adoption of (Western) coinage autonomously subdued passive and ‘primitive’ reciprocity and redistribution-based economies at the periphery. Many scholars now argue that cultural, religious and economic contexts directed exchange practices in Roman Egypt. This article argues that these embedding elements were themselves cultivated in a meta-context of place—namely, the fluvial geography and ecology of the Nile Valley, Delta and Fayyum Oasis. The rhythmic inundations of the Nile and Egypt’s related agricultural cycle shaped the meanings inhabitants attached to instruments of exchange, including the invading coins of Greek and Roman polities. Coinage thoroughly permeated Egyptian institutions, and yet ecologically-determined rituals, customs and traditions preserved aspects of indigenous exchange culture. Ecological forces nurtured and strengthened the cultural, economic and political forces that constrained Roman monetary imperialism. The monetization of Roman Egypt is, therefore, a critical historical case-study of broader geographic, temporal and thematic interest—one which enables scholars to better understand how ecology intersects with cultural, economic and political embeddedness.
Proximity, NIMBYism, and Public Support for Energy Infrastructure
(2020) Konisky, David M; Ansolabehere, Stephen; Carley, Sanya
The public opinion literature examining the role of proximity and not-in-my-backyard (NIMBY) attitudes in people’s judgments about energy projects has come to inconclusive findings. We argue that these mixed results are due to vast differences and significant limitations in research designs, which we mitigate through a large study (n = 16,200) of Americans’ attitudes toward energy projects. Our approach examines a diverse set of energy projects in development, explicitly compares the attitudes of individuals living in the vicinity of projects with those farther away, and includes the careful measurement of the NIMBY concept. The analyses show little evidence that proximity in general or NIMBY objections in particular are important determinants of project support. Instead, other factors are more important, including perceptions of local environmental quality, risk orientation, concern about climate change, and trust in energy companies.

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