جستجوی استاد راهنمای دانشگاهی

Jennifer J. Edmondsمشاهده پروفایل

استاد

• Business Administration
• Management Science
• Operations Management
• +۶ مورد دیگر

Dr. Jennifer J. Edmonds serves as Dean of the School of Business & Digital Media and Professor of Business Administration at Georgian Court University, a position she has held since 2019. Previously, she was Associate Dean at the Sidhu School of Business & Leadership at Wilkes University from 2016-2019 and held various academic positions there from 2004-2019, including Department Chair of the Finance, Accounting & Management Department from 2013-2016. Dr. Edmonds earned her educational credentials from prestigious institutions: PhD in Management Science, Rutgers University, 2004 Master of Business Administration, Rutgers University, 2004 Bachelor of Science in Chemical Engineering, University of Michigan, 1997 Her research spans multiple domains within business and management, with particular expertise in operations management, statistics, and business education technology. Dr. Edmonds has developed innovative frameworks for employee motivation and leadership development, while also contributing to the understanding of how political events impact economic indicators like exchange rates. Her work bridges theoretical concepts with practical business applications, often focusing on the integration of technology in business education and operations. Dr. Edmonds' scholarly output demonstrates a consistent trajectory from technical operations research early in her career toward broader business management applications. Her publications reflect expertise across multiple business disciplines including statistics, operations management, leadership, and business education technology. She has made significant contributions to understanding adaptive testing methodologies, exchange rate dynamics, and the integration of mobile technology in business education. Dr. Edmonds has held significant administrative roles including Director of Graduate Programs at Wilkes University (2018-2019) and Department Chair of the Finance, Accounting & Management Department (2013-2016), demonstrating leadership in academic program development and management. Her career progression from Assistant Professor to Dean reflects her contributions to business education and administration. Early in her career, Dr. Edmonds worked as a Process Engineer at Dow Corning Corporation, providing practical industry experience that informs her academic work in operations management and business administration.

Christine DeMarsمشاهده پروفایل

استاد

• Educational Measurement
• Psychometrics
• Item Response Theory (IRT)
• +۴ مورد دیگر

Christine DeMars is a Professor of Graduate Psychology and Senior Assessment Specialist at James Madison University (JMU), affiliated with the Center for Assessment & Research Services (CARS). She holds a PhD in Measurement and Quantitative Methods from Michigan State University (1998), an M.Ed. in Elementary Education from Arizona State University (1993), and a B.A. in Psychology from Wichita State University (1990). Her research focuses on psychometric methods, including item response theory (IRT), differential item functioning (DIF), equating, and large-scale testing challenges. She teaches courses in IRT and classical test theory and supervises PhD students. As CARS liaison to Cluster 4 (Stewardship and Sustainability) and Communications Studies (SCOM), she advises on assessment design and implementation. Recent work addresses low-stakes testing validity, remote assessment integrity, and pandemic-related testing adaptations. Her publications emphasize methodological rigor and practical applications in educational measurement. Her scholarly contributions include over 50 peer-reviewed articles on topics like response validity, IRT parameter recovery, and DIF detection. Her work bridges theoretical advancements and real-world testing challenges, particularly in addressing examinee motivation, external event impacts, and model misfit implications. She collaborates with institutions to enhance assessment practices through evidence-based strategies. Ms. DeMars is actively involved in professional development, offering workshops on assessment design and psychometric analysis. Her efforts in CARS support institutional learning outcomes and program evaluation initiatives, reflecting her commitment to advancing educational measurement practices.

Yi-Hsin Chenمشاهده پروفایل

استاد

• Educational Measurement
• Psychometrics
• Cognitive Diagnostic Modeling
• +۳ مورد دیگر

Dr. Yi-Hsin Chen is a Professor in the Department of Educational Measurement and Research at the College of Education, University of South Florida (USF), located on the Tampa campus in office EDU 362. Her teaching responsibilities include: EDF 6432: Foundations of Measurement (Online) EDF 6407: Statistical Analysis for Educational Research I (Online) EDF 7439: Item Response Theory EDF 7469: Computer-Based Testing EDF 7436: Rasch Models Her primary research focuses on cognitive psychometric models including GDINA, LCDM, and DINA, which integrate cognitive attributes into measurement frameworks. She specializes in diagnostic classification modeling, cross-cultural validation of educational constructs, and development of computer-based assessments. Her work bridges theoretical psychometrics with practical applications in mathematics and literacy assessment. Analysis of her recent publications reveals consistent innovation in cognitive diagnostic modeling, particularly in mathematics education (TIMSS, van Hiele geometry), orthographic processing, and cross-cultural validation. Her research increasingly incorporates computational methods like Bayesian estimation and R programming while addressing emerging challenges such as AI-generated test items. The interdisciplinary nature of her work spans educational psychology, statistics, and international assessment.

Cindy J Nowinskiمشاهده پروفایل

استاد پژوهش

• Health Services Research
• Clinical Research
• Healthcare Quality
• +۷ مورد دیگر

Cindy J Nowinski, MD, PhD is a Research Professor in the Departments of Medical Social Sciences (Outcome and Measurement Science, Determinants of Health, Implementation Science) and Neurology (Ken and Ruth Davee Department) at Northwestern University Feinberg School of Medicine. She is affiliated with the Institute for Public Health and Medicine (IPHAM) - Center for Patient-Centered Outcomes and the Northwestern University Clinical and Translational Sciences Institute (NUCATS). Dr. Nowinski earned her BS (1982), MA (1986), and PhD (1991) from Loyola University of Chicago, followed by an MD (2000) from Northwestern University Feinberg School of Medicine. Trained as both a clinical psychologist and physician, she brings a unique interdisciplinary perspective to her research. With over 20 years of experience, Dr. Nowinski is a leading expert in developing patient-reported outcome measures and performance-based cognitive assessments for children and adults. Her research focuses on improving health and healthcare quality through standardized outcome measures, with particular emphasis on cognitive aging, neurological conditions (dementia, multiple sclerosis), and digital assessment technologies. She has played central roles in major national initiatives including Neuro-QoL, PROMIS, NIH Toolbox, Mobile Toolbox, and MyCog. Her recent publications reveal a strong emphasis on smartphone-based cognitive screening tools for primary care implementation, machine learning optimization of assessment algorithms, and validation of remote cognitive testing methods. This work demonstrates her commitment to translating research into practical clinical tools that improve early detection of cognitive impairment. Dr. Nowinski has received the Innovations Award from NorthShore University HealthSystem (2007) and holds numerous leadership positions including: Member, Digital Measures: Alzheimer's Disease and Related Dementias Working Group, Digital Medicine Society (2022-Present) Member, Clinical Practice Special Interest Group Working Group on PROMs as Screening Tools, International Society for Quality of Life Research (2020-Present) Associate Editor, Quality of Life Research (2018-2021) Guest Editor, Frontiers in Pediatrics (2019-2022) She maintains active involvement in multiple professional societies including PROMIS Health Organization, Alzheimer's Association ISTAART, Digital Medicine Society, and International Society for Quality of Life Research. Her research is conducted through collaborations focused on implementing digital cognitive assessment tools like MyCog and Mobile Toolbox in diverse clinical settings, with special attention to underserved communities.

Benjamin W. Domingueمشاهده پروفایل

دانشیار

• Psychometrics
• Sociogenomics
• Quantitative Methods
• +۳ مورد دیگر

Benjamin W. Domingue is an Associate Professor at the Graduate School of Education , Stanford University, with affiliations including the Stanford Center on Early Childhood and Policy Analysis for California Education (PACE) . His research bridges psychometrics and sociogenomics , focusing on statistical tools for measuring educational outcomes and integrating genetic data into social science research. Education: PhD in Education, University of Colorado Boulder (Advisor: Derek Briggs, 2012) MA in Mathematics, University of Texas at Austin (Advisor: Uri Treisman, 2006) BS in Mathematics, University of Texas at Austin (2001) His work examines test score properties , response time analysis , and genetic influences on educational attainment . Recent projects include developing the Item Response Warehouse (IRW) resource and analyzing oral reading fluency during the pandemic . Key methodological contributions involve the InterModel Vigorish (IMV) for predictive accuracy and speed-accuracy tradeoffs in real-world settings. Scientific Awards Jacobs Foundation Research Fellow (2022–2024) Outstanding Reviewer for AERA Open (2019, 2018) AERA Division D Quantitative Dissertation Award (2013) Faculty Advising Award (2018–2019) His research spans collaborations with institutions like the University of California, Berkeley, University of Colorado Boulder, and The University of Texas at Austin. He has contributed to genetic moderation studies , item response theory , and healthcare provider behavior through psychometric approaches.

• Educational Measurement
• Statistics
• Testing and Assessment
• +۳ مورد دیگر

Robert Ankenmann is an Associate Professor in the Department of Psychological and Quantitative Foundations at the University of Iowa's College of Education. He is affiliated with the Iowa Testing Programs (ITP) and specializes in Educational Measurement and Statistics. His academic background includes a PhD in Educational Research Methodology from the University of Pittsburgh, alongside degrees from the University of Waterloo and the University of Western Ontario. Ankenmann has received notable awards, including the Collegiate Teaching Award (1998) and recognition for his dissertation (1994). His research focuses on statistical methodologies in educational testing, including differential item functioning (DIF), item response theory (IRT), and assessment design. Education: PhD in Educational Research Methodology, University of Pittsburgh MED in Educational Foundations, University of New Brunswick BED in Secondary Mathematics Education, The University of Western Ontario BMath in Mathematics, University of Waterloo Research interests span educational measurement, psychometrics, and statistical methods applied to testing systems. He has contributed to advancements in computerized adaptive testing (CAT), item exposure control, and validation of performance assessments. His work emphasizes practical applications in K-12 and higher education contexts, often addressing challenges in test design and fairness. Awards highlight his teaching excellence and scholarly contributions. Recent grants include leadership on a GAANN fellowship program (2013-2017) and studies comparing multiple-choice vs. constructed-response assessments (2003-2005). He actively mentors doctoral students in quantitative research methodologies. Ankenmann collaborates with the Iowa Testing Programs (ITP), contributing to large-scale assessment development. His professional affiliations include the National Council on Measurement in Education and the American Educational Research Association.

Shiyang Suمشاهده پروفایل

دانشیار

• employee well-being
• workplace adaptability
• workplace deviance

Shiyang Su is an Associate Professor in the Industrial/Organizational Psychology program at the University of Central Florida. Her research applies advanced statistical models to study employee well-being, adaptability, and workplace deviance. She directs the Psychometrics Lab and has secured over $1 million in grants from agencies like the Army Research Institute. Education: She holds a Ph.D. in Educational Psychology (Measurement) and an M.S. in Statistics from the University of Minnesota. Research Focus: Her work examines dynamic workplace phenomena, including job insecurity, professional isolation, and work-school conflicts, using longitudinal and machine-learning methods. She develops psychometric tools for precise behavioral measurement. Publications: Recent articles analyze COVID-19's impact on remote work isolation, trajectories of workplace incivility, and adaptive testing for cognitive assessment in healthcare. Her research emphasizes real-world applications in organizational settings. Teaching: She offers courses in research methods, psychometrics, and data analysis, bridging theory with computational approaches.

Gina Biancarosaمشاهده پروفایل

استاد

• Reading Comprehension
• Reading Assessment
• Adolescent Literacy
• +۵ مورد دیگر

Gina Biancarosa holds the Ann Swindells Chair in Education as a Professor in the Department of Special Education and Clinical Sciences within the University of Oregon's College of Education, where she also maintains a courtesy appointment in the Quantitative Research Methods in Education PhD program. Her research at the Center on Teaching and Learning focuses on refining reading comprehension measurement and modeling longitudinal reading growth, leading to significant tools like MOCCA for Grades 3-5 and DIBELS 8th Edition spanning kindergarten through eighth grade. Her educational foundation includes: EdD in Language and Literacy (2006) from Harvard University EdM in Language and Literacy (1999) from Harvard University BA in English Literature (1992, summa cum laude) from Boston College Biancarosa's research centers on reading assessment, comprehension, adolescent literacy, and longitudinal analysis, employing advanced methodologies including hierarchical linear modeling and IRT. She has pioneered diagnostic measures that provide teachers with actionable data, shifting assessment paradigms toward cognitive process evaluation rather than isolated skill metrics. Her work bridges psychometric rigor with classroom applicability, particularly in identifying at-risk readers through subscore analysis and adaptive testing. Recent publications reveal a trajectory toward innovative measurement techniques, including computer-adaptive assessments and pandemic impact studies on reading fluency. Her scholarship consistently addresses the intersection of cognitive theory, measurement science, and practical literacy instruction, with growing emphasis on bilingual contexts and technology-enhanced assessment. Her scientific recognition includes: 2024 Significant Contribution to Educational Measurement Award (AERA) 2023 Outstanding Service Award (UO College of Education) 2021 Distinguished Excellence in Research/Outreach Award 2016 Ann Swindells Chair in Education Spencer Foundation Midcareer Training Grant (2016) Biancarosa has secured over $8 million in external funding from IES, Spencer Foundation, Alaska Department of Education, and Carnegie Corporation, plus $100,000+ in internal grants. She actively mentors doctoral students (seeking new candidates for 2025-2026) and teaches measurement, assessment, and applied statistics courses while serving on editorial boards for top journals including Reading Research Quarterly. Her current lab work at the Center on Teaching and Learning includes validating computer-adaptive MOCCA and developing Alaska Native language literacy screeners, supported by a student research seminar examining national reading trends and DIBELS 8th Edition validation.

Miguel Blacuttمشاهده پروفایل

استاد بالینی

• Mental Health
• Suicide Prevention
• Clinical Psychology
• +۳ مورد دیگر

Miguel Blacutt is a Clinical Professor with expertise in mental health and clinical psychology. His research focuses on understanding biological, psychological, and environmental risk factors for self-injury and suicide, as well as developing prevention strategies. He holds a BSc from McGill University and an Ed.M. from Columbia University's Teachers College. His work spans diverse topics including maternal stress impacts on infant temperament, smartphone usage and suicide risk, and motivation states for physical activity. He has published extensively on behavioral assessment tools and intervention design, particularly using longitudinal data and computational methods. Miguel’s research also explores pandemic mental health effects, wearable technology applications for tremor management in Parkinson’s disease, and cultural adaptations of clinical scales. He collaborates on projects analyzing motivation dynamics and mental health disparities across populations.

Hans Friedrich Köhnمشاهده پروفایل

دانشیار

• Cognitive Diagnosis
• Psychometrics
• Combinatorial Data Analysis
• +۳ مورد دیگر

Hans Friedrich Köhn is an Associate Professor in the Department of Psychology at the University of Illinois Urbana-Champaign, specializing in quantitative methods at the intersection of psychometrics, statistics, and cognitive psychology. His research program centers on three interconnected pillars: Combinatorial Data Analysis : Developing techniques for analyzing individual differences through multiple proximity matrices derived from diverse data sources including subjects, experimental conditions, and temporal measurements. Nonmodel-Based Clustering : Advancing large-scale clustering methodologies with particular emphasis on the $$p$$-median model for psychological data partitioning. Cognitively Diagnostic Modeling : Innovating in cognitive diagnosis theory including attribute hierarchy models, $$Q$$-matrix identifiability, and the duality of diagnostic classification frameworks like DINA and DINO. Analysis of his 15 most recent publications (2015-2025) reveals overwhelming concentration on cognitive diagnosis (87% of works), with $$Q$$-matrix theory constituting the dominant thread. His contributions span theoretical foundations (identifiability conditions, consistency proofs) and practical implementations (two-step estimation algorithms, heuristic approaches for unknown $$Q$$-matrices). The p-median clustering work remains consistently integrated, particularly in combinatorial data analysis contexts. Recent 2024-2025 publications demonstrate active expansion into nonparametric cognitive diagnostic computerized adaptive testing (CD-CAT) and MCMC methodology for latent variable models. Dr. Köhn maintains scholarly influence through critical commentaries on foundational works (e.g., Greenhouse-Geisser correction) and reference contributions like the Wiley StatsRef entry on Hierarchical Cluster Analysis, establishing him as a key contributor to psychometric methodology development.

• Sports Medicine
• Concussion Assessment
• Traumatic Brain Injury
• +۳ مورد دیگر

Scot Raab, PhD, serves as Associate Dean of the College of the Environment, Forestry, and Natural Sciences (CEFNS) and holds the academic rank of Associate Professor in the Department of Physical Therapy and Athletic Training at Northern Arizona University (NAU). His dual role encompasses both administrative leadership within the college and active research/teaching responsibilities in health sciences. Research Focus: Dr. Raab's scholarly work centers on sports medicine and neurophysiological assessment of traumatic brain injury , with particular expertise in: Quantitative EEG analysis for mild TBI diagnosis Concussion assessment protocols using computerized testing King-Devick Test validation across different media Athletic performance optimization and injury recovery Biomechanical factors in sports injuries His recent publications demonstrate a clear trajectory toward clinical applications of neurophysiological markers in concussion management, particularly through advanced EEG methodologies. The 2024 study in NeuroRegulation represents groundbreaking work in differentiating mild TBI patients using quantitative EEG parameters. Research Impact: While no specific awards are listed, his work has garnered significant attention with 21 Scopus citations and 1,174 readers on Mendeley for his 2020 King-Devick Test study alone. His h-index of 2 reflects early-career impact in specialized fields. Collaborations: Dr. Raab maintains active research collaborations with international partners, as evidenced by external collaboration metrics. His work involves multidisciplinary teams combining expertise in neurophysiology, athletic training, and clinical assessment.

• Stroke Recovery
• Neurorehabilitation
• Neural Control of Locomotion
• +۶ مورد دیگر

Steven A. Kautz, PhD is Professor and Chair of the Department of Health Sciences and Research at the Medical University of South Carolina (MUSC) College of Health Professions. With extensive research experience spanning over three decades, Dr. Kautz is a leading expert in stroke rehabilitation, neurorehabilitation, and the biomechanics of human movement. His work uniquely bridges engineering principles with clinical rehabilitation to improve functional outcomes for individuals with neurological impairments. Dr. Kautz's research focuses on: Stroke recovery mechanisms and rehabilitation strategies Neurorehabilitation techniques including transcranial direct current stimulation Neural control and biomechanics of locomotion Muscle coordination patterns in post-stroke gait Quantitative assessment of motor function and recovery His recent publications demonstrate continued leadership in stroke rehabilitation research with emerging work in connective tissue disorders. Current investigations include advanced neuroimaging techniques, gait analysis, and innovative rehabilitation approaches, often through large collaborative efforts such as the ENIGMA Stroke Recovery Working Group. His work has significant translational impact on clinical rehabilitation practices.

• Psychometrics
• Bayesian Statistical Methods
• Educational Assessment
• +۳ مورد دیگر

Alfonso J. Martinez is an Assistant Professor of Psychology at Fordham University's Department of Psychology. His research focuses on advanced statistical methodologies in psychometrics, particularly Bayesian approaches, latent variable modeling, and diagnostic classification systems. He contributes to improving measurement techniques in educational and psychological assessments through innovative model development and validation. His work addresses challenges in personality assessment, rapid guessing behavior in testing, and the application of structural equation modeling (SEM) across diverse contexts. He actively publishes in high-impact journals, with a focus on methodological advancements and their practical implications for assessment design. While no specific academic awards are listed, his prolific publication record reflects dedication to advancing statistical methodologies in psychology. His teaching and professional affiliations include involvement with academic organizations central to psychometric research and educational measurement.

Yu Baoمشاهده پروفایل

استادیار

• Diagnostic Classification Modeling
• Computerized Adaptive Testing
• Psychometrics
• +۴ مورد دیگر

Yu Bao is an Assistant Professor in the Department of Graduate Psychology at James Madison University (JMU) and serves as an Assistant Assessment Specialist in the Center for Assessment and Research Studies (CARS). She joined JMU in 2019 and holds a Ph.D. in Quantitative Methodology from the University of Georgia, an M.S. and B.S. in Statistics from Beijing Normal University. Her scholarly interests include diagnostic classification modeling, computerized adaptive testing, and psychometric methods. She leads the Program Assessment Support Services (PASS) in CARS, collaborating with four graduate students to support JMU’s academic program reviews, assessment reporting, and faculty development workshops. Her research focuses on advancing assessment methodologies in education and neuroscience, including applications of machine learning in brain connectivity analysis and large language model evaluation. She has contributed to studies on child behavioral risk assessment, self-regulated learning in MOOCs, and cross-cultural analyses of educational barriers. Yu Bao’s work bridges statistical theory with practical educational challenges, emphasizing the ethical and technical dimensions of AI-driven assessment systems. Her publications span neuroimaging data analysis (e.g., functional connectivity networks in human and macaque brains) and educational assessments (e.g., validation of behavioral screening tools in Chinese schools, OER adoption barriers). She actively engages in interdisciplinary collaborations, addressing topics like gender disparities in creativity identification and AGI ethics. Yu Bao’s role in CARS ensures alignment between institutional assessment practices and academic excellence, particularly during disruptions like the pandemic.

• Cancer survivorship
• Symptom management
• Health-related quality of life (HRQOL)
• +۳ مورد دیگر

Rina Fox is an Assistant Professor and clinical health psychologist at the University of Arizona, where she serves as Co-Director of the Cancer Center's Behavioral Measurement and Interventions Shared Resource. Her research focuses on psychosocial processes affecting cancer survivorship, with a specific emphasis on sleep health, symptom management, and digital behavioral interventions to enhance health-related quality of life (HRQOL). B.A. Psychology & Spanish, Tufts University M.P.H. Epidemiology, San Diego State University M.S./Ph.D. Clinical Psychology, San Diego State University/University of California: San Diego joint doctoral program Her work integrates behavioral intervention optimization methods (e.g., MOST framework) and digital delivery systems to improve access to psychosocial care for cancer survivors. She has published extensively on topics including sleep duration, dietary quality, physical activity, and social connectedness in cancer populations. Key trends in her publications include: Development of tailored digital behavioral interventions (e.g., TOGETHER, Fit2ThriveMIND) Application of computerized adaptive testing (NIH Toolbox) in clinical settings Exploration of sleep/circadian interventions for gynecologic and breast cancer survivors Systematic reviews on social isolation and connectedness Feasibility studies for novel interventions in narcolepsy and scleroderma Scientific recognition includes Top 10% most-viewed Cancer article in 2023 for her systematic review on social connectedness in young adult cancer survivors. The REACH (Research and Education to Advance Cancer survivor Health) Lab, which she leads, develops and tests interventions to address symptom clusters, sleep disturbances, and quality-of-life challenges in cancer survivors. Her team utilizes human-centered design and stakeholder engagement to refine digital health tools like the TOGETHER intervention platform.