جست‌وجوی استاد و پژوهشگر

• Learning Analytics
• Educational Technology
• Virtual Reality Education
• +۵ مورد دیگر

Ulrik Schroeder is a Universitätsprofessor (Full Professor) at RWTH Aachen University, leading the Chair of Learning Technologies within the Faculty of Computer Science. His research focuses on the intersection of educational technology, learning analytics, and immersive technologies with particular emphasis on practical implementations in higher education settings. Professor Schroeder's research spans multiple interconnected domains in educational technology. His primary interests include Learning Analytics implementation (particularly using xAPI standards), Virtual Reality applications for education, Open Educational Resources development and conversion, and gamification approaches for programming education. He has developed several notable tools including convOERter for OER conversion, WebWriter for creating explorable explanations, and various xAPI-based learning analytics infrastructures. His work consistently bridges theoretical frameworks with practical educational applications, often focusing on computer science education contexts. Analysis of his recent publications reveals a strong trend toward integrating Learning Analytics with immersive technologies, particularly Virtual Reality environments. His research demonstrates a systematic approach to educational technology development, with emphasis on scalability, interoperability through standards like xAPI, and practical implementation in real educational settings. The work increasingly focuses on personalized learning paths, quality assurance for educational resources, and privacy-conscious data collection. Co-editor of 21. Fachtagung Bildungstechnologien (DELFI) (2023) Co-editor of Hochschuldidaktik der Informatik HDI 2018 Co-editor of DeLFI 2018 conference proceedings Professor Schroeder has supervised numerous doctoral and postdoctoral researchers who frequently appear as co-authors on his publications, indicating an active research group. His projects often involve interdisciplinary collaborations across computer science, education, and psychology. Current major initiatives include the AIStudyBuddy project for study path analysis and the development of VR classroom simulations for teacher training. His research group, the Learning Technologies Innovation Lab, develops open research tools that support various aspects of educational technology research and implementation.

• Software Testing
• Mutation Testing
• Model-Based Testing
• +۷ مورد دیگر

Jeff Offutt is a Professor and Chair of the Department of Computer Science at the University at Albany, College of Nanotechnology, Software, & Engineering. Previously, he was a Full Professor with Tenure in Software Engineering at George Mason University since 2005. He received his PhD in Information & Computer Science from the Georgia Institute of Technology in 1988. His research spans software testing, mutation testing, model-based testing, automatic test data generation, web application testing, and software engineering education. He has led significant projects such as the NSF-funded integration of CS into K-5 classrooms and the Google-funded SPARC project for scalable CS1/CS2 instruction. The 15 most recent articles reflect a continued focus on mutation testing cost reduction, model-based testing oracles, educational innovations, and security aspects of web applications. Trends include empirical validation, industrial applicability, and bridging theory with practice in software testing and engineering education. John Toups Presidential Medal for Excellence in Teaching (2020) George Mason University’s Alumni Association Faculty Member of the Year (2020) Outstanding Faculty Award from the State Council of Higher Education for Virginia (2019) Best Paper Award at ICST 2021 10-Year Most Influential Paper Award at MODELS 2020 George Mason University Teaching Excellence Award (2013) ACM Notable Article Award (2013) Jeff Offutt has mentored numerous graduate students including Upsorn Praphamontripong, Nan Li, and Yu-Seung Ma, and has led major grant-funded projects such as the SPARC educational model and NSF initiatives on K-5 CS integration. His textbook Introduction to Software Testing (with Paul Ammann) is widely adopted globally. He led the MS in Software Engineering program at GMU and developed several new courses in software testing, web engineering, and usability. He pioneered innovative teaching methods using web technologies and asynchronous learning models. He also co-founded the IEEE International Conference on Software Testing, Verification and Validation (ICST) and served as Editor-in-Chief of Software Testing, Verification and Reliability from 2007 to 2019.

Murali Maniمشاهده پروفایل

استاد

• Database Systems
• Data Provenance
• Generative AI
• +۱۲ مورد دیگر

Murali Mani is a Professor in the Department of Computer Science, Engineering, and Physics at the College of Innovation and Technology, University of Michigan-Flint. He is actively involved in teaching courses such as Database Design (CSC 384, CSC 584) and Independent Graduate Study in Computer Science (CSC 591), and serves as Principal Investigator on multiple research grants focused on computing education and data science. His research interests span database systems, data provenance, generative AI for data augmentation, computing education, and the societal impact of technology . He has developed educational tools including epidemiology calculators and market basket analysis modules to support interdisciplinary learning. His work emphasizes integrating computing skills across disciplines such as health sciences and management. The 15 most recent scholarly contributions reflect a strong focus on data management, AI-augmented data curation, educational technology, and the cognitive aspects of learning programming. These publications appear in venues such as VLDB, IEEE FIE, and ACM conferences, with several under review or in preparation for top-tier journals like Communications of the ACM and the VLDB Journal. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: Murali Mani actively mentors students through independent graduate studies and collaborative research projects. He has secured funding from the National Science Foundation (SGER grant on provenance metadata) and internal university sources, including the CIT/CHS Joint Grant and the Office of Research at UM-Flint, supporting projects on civic literacy, computational skills integration, and AI for social science data archiving. Labs and Teams: While no formal lab name is mentioned, Murali Mani leads a research group focused on data systems and computing education, collaborating with colleagues across departments and institutions. He contributes to initiatives such as the Michigan Institute for Data & AI in Society (MIDAS) and the Academic Data Science Alliance (ADSA), and has presented at conferences including IASSIST, FIE, and ICCTAC.

Bruce A. Maxwellمشاهده پروفایل

استاد آموزشی

• Computer Vision
• Robotics
• Computer Graphics
• +۳ مورد دیگر

Bruce A. Maxwell is a Teaching Professor and Assistant Director of Computing Programs at Northeastern University’s Seattle Campus, following roles as Chair of the Computer Science (CS) Department at Colby College (2013–2020) and leadership in establishing the Khoury College MS CS Align Program at the Roux Institute (2020–2022). His academic journey includes affiliations with Northeastern’s Seattle Campus and ongoing collaboration with Colby CS as a research scientist. He specializes in Computer Vision, Robotics, Computer Graphics, Game Design, and Data Analysis, with notable contributions to concussion management research through the Maine Concussion Management Initiative (MCMI), focusing on sports-related injury analysis and symptom monitoring. His research spans over two decades, with significant work in human-robot interaction, autonomous systems, and educational technology. Notable projects include developing tools for real-time shadow removal in autonomous driving contexts and analyzing cognitive outcomes in student-athletes post-concussion. Maxwell has authored over 50 peer-reviewed publications, emphasizing interdisciplinary approaches bridging computer science, sports medicine, and educational policy. Teaching innovations include integrating thematic elements (e.g., Lord of the Rings) into CS1 coursework and advocating for writing in computer science curricula. He maintains active roles in academic service, including SIGCSE conference contributions and panel discussions on gender equity in tech education. Education: Ph.D. in Robotics from Carnegie Mellon University (1996), M.Phil. in Engineering from Cambridge University (1993). Awards: Recognized for pedagogical contributions but no named awards listed in provided materials. Labs/Teams: Collaborates with the Maine Concussion Management Initiative and Khoury College’s Align Program team.

Martin Henzمشاهده پروفایل

دانشیار

• Programming Languages
• Software Engineering
• Artificial Intelligence
• +۸ مورد دیگر

Martin Henz is an Associate Professor at the National University of Singapore , affiliated with the School of Computing and its Department of Computer Science . His academic journey includes an M.Sc. in Computer Science from Stony Brook University (1993) and a Dr.rer.nat. in Computer Science from Saarland University (1997). He has also worked as a Research Scientist at the German Research Centre for Artificial Intelligence. Research Focus : Scalable Experiential Learning, Systems for Teaching/Learning, AI in Education, Programming Languages, Algorithms, and Constraint Programming. Key Projects : Source Academy (immersive programming environment), Deep Teaching (LMS enhancements), and NUS Seafarers (maritime experiential learning). Publications span education technology, programming languages, and sustainable engineering, with recent works focusing on JavaScript-based pedagogy, automated question generation, and electric vehicle conversions. He supervised Rahul Singhal 's PhD, leading to the educational startup Cerebry, and co-founded Workforce Optimizer Pte Ltd with Alan Sevugan. Awards : NUS Annual Digital Education Award (2021) NUS Annual Teaching Excellence Award (2016/17) Fulbright Scholarship (1990) Startup @ Singapore Champion (2001)

Giulia Totiمشاهده پروفایل

استادیار

• Computer Science Education
• Ethics in Data Science
• Machine Learning
• +۳ مورد دیگر

Giulia Toti is an Assistant Professor of Teaching in the Department of Computer Science at the University of British Columbia (UBC), part of the Faculty of Science. Her work focuses on computer science education, equity in curriculum design, and fostering inclusive learning environments. She teaches courses such as Applied Machine Learning (CPSC 330), Fairness, Accountability, Transparency, and Ethics (FATE) in Data Science (DSCI 430), and Computers and Society (CPSC 430). Her research explores diversity initiatives in CS education, mastery learning frameworks, and equitable grading practices. Notable contributions include studies on pandemic-era remote teaching impacts and the development of Agora, a tool for enhancing large-classroom engagement. Toti has received UBC Faculty Teaching Awards for her pedagogical innovations. Her interdisciplinary work spans machine learning applications in industry and healthcare, including semantic search systems for clinical data (SemEHR) and predictive analytics for energy production. She is affiliated with the ACE Lab and actively contributes to curriculum reforms addressing DEI (Diversity, Equity, Inclusion) challenges in STEM education. Grants/Awards: Faculty Teaching Awards Labs/Teams: ACE Lab (Advancing Computing Education) Advising: No explicit advisee listings found, but contributes to pedagogical research impacting teaching practices.

Matthew Hertzمشاهده پروفایل

استاد آموزشی

• Computer science education
• runtime systems
• dynamic memory management

Matthew Hertz is a Teaching Professor in the Department of Computer Science and Engineering at the University at Buffalo's School of Engineering and Applied Sciences. His research focuses on computer science education, runtime systems, and dynamic memory management. Education: PhD, Computer Science, University of Massachusetts Amherst, 2006 MS, Computer Science, University of Massachusetts Amherst, 2001 BA, Computer Science, Carleton College, 1997 Research interests span computer science education and systems optimization. His educational research investigates learning factors in introductory programming courses, develops pedagogical tools like CloudCoder for programming exercises, and analyzes failure rates in CS1 courses. In systems research, he focuses on memory management innovations including garbage collection algorithms, adaptive resource allocation, and performance optimization in shared environments. Publications show dual focus: recent work emphasizes educational data analysis and programming pedagogy while earlier research concentrates on memory management efficiency and runtime systems. Trends include automated assessment tools and adaptive algorithms for resource-constrained environments. No scientific awards reported. No advising or grant information available. No labs or teams mentioned in available data.

Jessica Young Schmidtمشاهده پروفایل

دانشیار

• Computer Science Education
• Active Learning
• Instructional Design
• +۲ مورد دیگر

Jessica Young Schmidt is an Associate Teaching Professor in the Department of Computer Science at North Carolina State University, serving as ABET Coordinator since 2017 and Course Coordinator for CSC226: Discrete Mathematics. Her primary focus is undergraduate education, particularly CSC116: Introduction to Computing – Java and CSC226, where she implements flipped classroom models and comprehensive end-of-semester exercises. Her educational background includes: Ph.D. in Computer Science, North Carolina State University, 2012 M.S. in Computer Science, North Carolina State University, 2009 B.S. in Computer Science and Mathematics, Roanoke College, 2007 Dr. Schmidt's research centers on computer science education, emphasizing active learning, instructional design, and software engineering pedagogy. She has pioneered methods like collaborative software engineering exercises for CS1 materials and frameworks for assessing critical thinking, with her work on end-of-semester integration earning a SIGCSE 2020 award. Her publications reveal an evolution from privacy policy analysis (2009-2012) toward educational innovation in recent years. Her scholarly contributions demonstrate consistent focus on curriculum development and assessment, particularly in integrating software testing throughout computer science education and enhancing student comprehension through structured reflection. She has received the following recognition: Third Best Paper, SIGCSE 2020 Technical Symposium (Experience Reports and Tools Track) As ABET Coordinator, Dr. Schmidt drives curriculum assessment and continuous improvement, while her CSC226 coordination ensures pedagogical consistency across sections. Her teaching innovations directly support student success in foundational computer science concepts.

• Computer Science Education
• Assessment and Feedback Systems
• Novice Programmer Development
• +۳ مورد دیگر

Dr Ryan Crosby is an Assistant Professor in the Department of Computer Science at Durham University. His research focuses on personalized assessment and feedback mechanisms in higher education, particularly addressing challenges faced by novice programmers. His doctoral work investigated the effectiveness of Ipsative Assessment in improving student experiences with assessment and feedback. Research interests include the assessment of introductory programming students, code quality evaluation in CS1 courses, and pedagogical strategies to enhance learning outcomes. Publications highlight collaborative work on curriculum design and assessment frameworks in computer science education. Publications emphasize interdisciplinary approaches to educational technology, with recent contributions focusing on code quality metrics and feedback methodologies. No awards or grants are explicitly mentioned, though his work contributes significantly to improving undergraduate programming education.

Lauren Margulieuxمشاهده پروفایل

دانشیار

• Computer Science Education
• Instructional Design
• Computational Literacy
• +۳ مورد دیگر

Lauren Margulieux serves as Associate Professor in the Department of Learning Sciences within Georgia State University's College of Education & Human Development. She founded and directs the Snap Inc. Center for Computer & Teacher Education, where she coordinates statewide teacher preparation programs to integrate computing across all disciplines. Her academic credentials include a Ph.D. and M.S. in Engineering Psychology from Georgia Institute of Technology and a B.A. in Psychology from Southwestern University. Her research focuses on computer science education for programming novices, computational literacy development, and instructional design for teacher training. Key initiatives include creating Georgia's computer science endorsement program for in-service teachers and developing models for computational thinking integration in K-12 education. Her work bridges cognitive science principles with practical classroom applications, particularly examining spatial skills, failure resilience, and self-efficacy in programming contexts. Current scholarly trends reveal deep engagement with generative AI integration in teacher education, computational activity design across disciplines, and neurocognitive aspects of learning from failure. Her publications consistently address equity in computer science pathways while developing robust assessment instruments for programming self-efficacy and spatial ability impacts. Margulieux leads significant outreach through the Snap Inc. Center, establishing partnerships with school districts to broaden participation in computer science education. Her work emphasizes practical implementation frameworks for teacher educators and develops resources for urban school contexts, particularly focusing on marginalized student populations. The center serves as both research hub and professional development engine for Georgia's teaching workforce.

Claus Brabrandمشاهده پروفایل

استاد

• Computing Education Research
• Gender Studies in STEM
• Diversity in Technology
• +۳ مورد دیگر

Claus Brabrand is a Professor of Software Engineering and Head of the Center for Computing Education Research at the IT University of Copenhagen. His research focuses on computing education, gender diversity in STEM, and software product line analysis. He has led projects like DIREC (Digital Research Centre Denmark) and ATTiKA (Adaptive Tools for Technical Knowledge Acquisition), funded by the Innovation Fund Denmark and Villum Foundation. PhD in Computer Science Over 45 publications in computing education and software engineering Active in curriculum development and educational policy Research interests include improving teaching quality through learning technologies, gender representation in IT materials, and cognitive competencies in programming education. His work bridges software engineering principles with pedagogical innovations, addressing issues like novice programmer performance and curriculum design.

Gina R. Baiمشاهده پروفایل

استادیار

• Software Engineering
• Computer Science Education
• Unit Testing
• +۵ مورد دیگر

Gina R. Bai is an Assistant Professor of the Practice in the Department of Computer Science at Vanderbilt University's School of Engineering. Her research focuses on software engineering and computer science education, particularly addressing student challenges in software testing and programming practices. She holds a B.S. in Computer Science from Wake Forest University (2016) and a Ph.D. from North Carolina State University (2022), advised by Kathryn T. Stolee. Her work explores testing checklists, generative AI's role in education, fairness in machine learning, and DEI in computing communities. Education: B.S. Computer Science (Wake Forest), Ph.D. Computer Science (NC State) Research Themes: Testing pedagogy, AI in education, DEI, code search Notable Projects: Testing checklist interventions, analysis of ChatGPT in CS1, fairness metrics Her publications emphasize student testing practices, the impact of educational tools, and ethical considerations in software development. She teaches courses like CS 1101 and CS 2201 at Vanderbilt, integrating research into curriculum design.

David Hovemeyerمشاهده پروفایل

عضو هیئت علمی

• Static Analysis
• Systems Software
• Computer Science Education
• +۳ مورد دیگر

David Hovemeyer is an Associate Teaching Professor at the Whiting School of Engineering, Johns Hopkins University . He holds a PhD (2005) and MS (2001) in Computer Science from the University of Maryland and a BA (1994) from Earlham College. Prior to joining JHU in 2019, he taught at Vassar College and York College of Pennsylvania. Education : PhD, MS, and BA in Computer Science Research : Focuses on static analysis , systems software , and computer science education Projects : FindBugs, CloudCoder, ProgSnap2, FunWithSound His recent work includes frameworks for declarative autograders , formats for programming process data , and tools for educational software development . He has been recognized with Excellence in Teaching Awards and contributes to open-source educational platforms like GitHub. Scientific Awards : 2024 Whiting School Teaching, Advising, and Mentoring Award Excellence in Teaching Award (multiple years) David maintains an active role in the academic community through peer instruction , programming contests, and recommendation letter advising . He also develops tools like FreePoll and Declarative Autograder Framework to enhance teaching efficiency.

Shuyin Jiaoمشاهده پروفایل

عضو هیئت علمی

• Computing Education
• Program Analysis
• Code Efficiency Analysis
• +۵ مورد دیگر

Shuyin Jiao is an active Associate Teaching Professor in the Department of Computer Science at North Carolina State University's College of Engineering. She serves as course coordinator for CSC 111 Introduction to Computing: Python and teaches multiple core undergraduate courses including CSC 116 (Java) and CSC 246 (Operating Systems), with extensive teaching experience spanning over 9 years at both NC State and the College of William & Mary. Her educational background includes a Ph.D. from the University of Houston (2015), a Diplôme d'Ingénieur from Ecole Central de Lyon, France, and a B.S. from Beihang University, China. She previously held positions as Assistant Teaching Professor (2020-2025) and Lecturer at NCSU, and taught as Lecturer and Adjunct Lecturer at William & Mary from 2015-2020. Dr. Jiao's research focuses on computing education and program analysis, with particular emphasis on developing tools to enhance student learning in computer science. Her work explores pedagogical methods to address diverse learning styles in increasingly large CS classrooms and investigates code inefficiencies through memory profiling and performance analysis. She leads the CERES lab at NCSU and serves as Publications Co-Chair for SIGCSE TS 2026. Her publication record shows consistent output in top venues including SIGCSE, CGO, MobiCom, and ICSE, with recent work spanning from 2025 back to 2012. Her research trajectory demonstrates a clear evolution from materials science (early career) to software engineering and computer science education, with current work heavily focused on educational technology and program analysis tools. Dr. Jiao has secured significant funding including as PI for NSF Grant DUE-#2417469 (2024-2027), NCSU Data Science Academy Seed Grant (2023-2024) as Co-PI, and NCSU GEARS Grants (2023-2024) as PI. She also serves as Co-PI for NSF Grant OAC-#2411136 (2025-2028) focused on computer system research. She actively involves undergraduate students in research through COE REU and CSC 498/499 projects, recruiting at CSC Undergraduate Research Lightning Talks each semester. Her course redesign projects include enhancing operating systems education through multimedia and redesigning CSC 111 with DELTA funding to address challenges in large-class instruction.

Collin F. Lynchمشاهده پروفایل

دانشیار

• Intelligent Tutoring Systems
• Adaptive Educational Technologies
• Argument Mining
• +۵ مورد دیگر

Collin F. Lynch is an Associate Professor in the Department of Computer Science at North Carolina State University, specializing in intelligent tutoring systems and adaptive educational technologies. His research addresses complex domains like scientific writing, law, and software development through AI integration. Education Ph.D. in Intelligent Systems (2014), University of Pittsburgh M.S. in Intelligent Systems (2011), University of Pittsburgh B.A. in Cognitive Science and Artificial Intelligence (2000), Hampshire College Research Focus Lynch's work combines artificial intelligence, learning science, and human-computer interaction. Key areas include: Argument mining and natural language processing Real-time classroom support for writing-to-learn Student modeling and hint generation Embodied cognitive agents in collaborative learning Social network impacts on education Grant Leadership Validating Automated Measures of Student Writing (2021-2026, $634,620, IES) RET Site: Socially Relevant Computing (2021-2025, $598,913, NSF) IGE: Learning the Entire Pipeline (2021-2024, $332,184, NSF) FLECKS: Collaborative CS Learning (2017-2023, $1,399,088, NSF) Integrated Teaching Platforms (2018-2022, $597,529, NSF) Evaluation for Actionable Change (2016-2021, $799,837, NSF) His projects often involve interdisciplinary collaboration and address challenges in blended learning environments, data-driven educational interventions, and socially relevant computing.