جستجوی استاد راهنمای دانشگاهی

• Educational Technology
• Informatics Education
• Programming Pedagogy
• +۳ مورد دیگر

Snježana Babić serves as Associate Professor and Head of the Graduate Study Program Informatics - Teaching Major at the Faculty of Informatics in Pula , University of Pula. With a PhD obtained in 2016 and university affiliation since 2017, she teaches across undergraduate and graduate programs focusing on ICT fundamentals, web design, digital competencies, and informatics education methodology. Her educational background includes graduation in 1993 followed by doctoral studies culminating in 2016. Though specific institutions aren't detailed in the text, her career trajectory shows progression from foundational ICT teaching to specialized informatics education leadership. Babić's research centers on educational technology adoption with particular emphasis on programming pedagogy for young learners through the MEMA method. Her work investigates digital competencies across multiple educational contexts, from primary schools to higher education. Recent publications demonstrate rapid adaptation to emerging technologies, with 2025 studies examining ChatGPT integration in Croatian educational settings and cross-cultural applications of programming methods. Analysis of her 15 most recent publications reveals consistent focus on technology acceptance models applied to Croatian educators and students. The research trajectory shows evolution from foundational e-learning systems (2016-2020) to cutting-edge AI and robotics applications (2022-2025), maintaining strong methodological focus on teacher motivation , implementation barriers , and culturally-specific adoption factors . Her teaching portfolio demonstrates deep integration with research interests: Undergraduate: ICT Fundamentals, Web Design and Application Graduate: Digital Competencies in Education, Informatics Education Methodology, Practicum for IT Educators Cross-disciplinary: ICT in Nursing, Healthcare Informatics Babić actively contributes to institutional leadership as program head while maintaining robust research productivity. Her work bridges theoretical technology adoption frameworks with practical implementation challenges in Croatian educational contexts, particularly examining how emerging technologies like humanoid robots and AI assistants can be effectively integrated into teaching practices.

Kelly K. Ivyمشاهده پروفایل

استادیار

• Mathematics Education
• Urban STEM Education
• Culturally Responsive Teaching
• +۳ مورد دیگر

Kelly K. Ivy, Ph.D. is an Assistant Professor at the University of the District of Columbia (UDC) in the College of Arts and Sciences. Specializing in culturally responsive math teaching and urban STEM education, she contributes to teacher self-efficacy research and curriculum development. Her work bridges academic inquiry with practical applications in K-12 and higher education contexts. Doctor of Philosophy in Mathematics Education, University of Maryland, College Park Master of Education in Curriculum & Instruction, Trinity Washington University Bachelor of Science in Mathematics, Secondary Education Professional Minor, Howard University Dr. Ivy’s research focuses on urban STEM education , culturally responsive pedagogy , and equitable mathematics instruction . She emphasizes teacher self-efficacy and interdisciplinary literacy, particularly in linguistically diverse classrooms. Her publications highlight strategies for improving STEM outcomes for African American students and reflective practices in culturally relevant teaching. Recent publications (2019–2024) span topics including equitable teaching , Black female STEM perspectives , and curriculum innovation . These works employ qualitative research methods and stress cultural relevance in urban settings. Faculty Scholar of Promise Award, UDC’s College of Arts and Sciences (2024) Dr. Ivy serves as Co-Project Manager for the Katherine G. Johnson Math Teacher Training Institute (2025–Present) and has participated in the Maryland Collaborative for Research in Urban STEM Education (2020–23). Her advocacy for Black students in STEM includes presentations at national conferences and media engagements.

Angeline Lillardمشاهده پروفایل

استاد

• Developmental Psychology
• Montessori Education
• Child Social and Cognitive Development
• +۳ مورد دیگر

Dr. Angeline Lillard is Commonwealth Professor of Psychology and Director of the Montessori Science Program at the University of Virginia. She leads the Early Development Lab, focusing on children's social and cognitive development, particularly Montessori education's impact on learning and wellbeing. A Fellow of AAAS, APA, and APS, she earned her BA in English Literature from Smith College and PhD in Psychology from Stanford University. Research Interests: Dr. Lillard's work bridges Montessori pedagogy with developmental psychology, analyzing how play, educational environments, and culturally responsive teaching shape child outcomes. She explores standardized testing disparities, discipline equity, and the neurobiological underpinnings of pretend play. Key themes in her 15 most recent publications include Montessori's role in reducing educational inequality, the cognitive effects of fantasy in media, and the use of multilevel modeling to assess school discipline patterns. Her research spans preschool to adult wellbeing, emphasizing self-determination theory and longitudinal data. Scientific Recognition: Awarded the Nancy Staub Award for Puppetry Research (2024) Recognized for her book with the Cognitive Development Society Book Award (2006) James McKeen Cattell Sabbatical Fellow (2005-06) Albert Bandura Graduate Research Award (2016-17) Advising and Grants: Mentored 15+ graduate students including Lee LeBoeuf and Christina Carroll. Secured IES funding for a 600-child study on public Montessori preschools and Arnold Foundation support for kindergarten data collection.

Laura Ascenzi-Morenoمشاهده پروفایل

استاد

• Bilingual Education
• Translanguaging
• Biliteracy
• +۷ مورد دیگر

Laura Ascenzi-Moreno serves as Professor of Bilingual Education and Bilingual Program Coordinator in the Childhood, Bilingual and Special Education Department at Brooklyn College, City University of New York (CUNY), School of Education. Her academic leadership focuses on developing educators capable of serving linguistically diverse student populations through equity-centered pedagogical frameworks. Her educational foundation includes a B.A. in Anthropology and Education from Swarthmore College (1994), an M.A. in Individualized Studies in Education from Harvard Graduate School of Education (1999), New York State Permanent Certification for PreK-6 (2002), a Bilingual ESL and Teacher Leadership Program from Bank Street College (2004), and a Ph.D. in Urban Education from CUNY Graduate Center (2012). Dr. Ascenzi-Moreno's research pioneers translanguaging applications across literacy instruction, assessment, and computational learning environments. She investigates how emergent bilinguals' linguistic repertoires can transform reading development, teacher knowledge construction, and multimodal assessment practices. Her work consistently centers equity through frameworks like syncretic reasoning and accompáñamiento, challenging deficit ideologies while promoting asset-based approaches to multilingual education. Analysis of her 2020-2024 publications reveals an accelerating interdisciplinary trajectory where translanguaging principles increasingly intersect with computer science education. This evolution demonstrates strategic expansion from foundational literacy research into computational literacies, with growing emphasis on co-design methodologies and teacher agency in developing multilingual CS curricula. Her scientific recognition includes the 2024 NCTE Outstanding Elementary Educator Award, Language Arts Distinguished Article Award, and major NSF grants totaling $1.3 million for computational literacy projects. Additional honors encompass Fulbright Scholarship work in Colombia, PSC-CUNY research awards, and Westinghouse Science Talent Search distinction. As Principal Investigator of NSF-funded PiLa-CS and former CUNY-NYSIEB Associate Investigator, she secures substantial grant support while mentoring teacher candidates. Her service includes NCTE Elementary Steering Committee leadership (2022-2026), journal reviewing, and Brooklyn's New York Teacher Table participation addressing educator recruitment/retention. Dr. Ascenzi-Moreno co-directs the Participating in Literacies in Computer Science project and maintains active collaboration with NYC schools through translanguaging professional development initiatives. Her work with the CUNY-NYSIEB project established foundational frameworks now implemented across New York bilingual programs.

Andrew Lanمشاهده پروفایل

دانشیار

• Artificial Intelligence in Education
• Educational Data Mining
• Personalized Learning
• +۵ مورد دیگر

Andrew Lan is an Associate Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst, where he also serves as the CS Undergraduate Program Director. He was granted tenure by the UMass Board of Trustees in June 2025 and is currently on leave through Spring 2026. His research focuses on developing human-in-the-loop machine learning methods to enable scalable, effective, and personalized learning experiences in education. Dr. Lan received his BS in Physics and Mathematics from the Hong Kong University of Science and Technology, followed by his MS (2014) and PhD (2016) in Electrical and Computer Engineering from Rice University. He completed postdoctoral research at Rice University (2016) and Princeton University's EDGE Lab (2017-2018). His research spans artificial intelligence for education, with particular expertise in educational data mining, knowledge tracing, personalized learning systems, and human-AI collaboration in educational contexts. Dr. Lan's work leverages massive and multimodal learner and content data collected from both traditional classrooms and online learning platforms to develop systems that deliver high-quality, affordable, and personalized learning experiences. He has made significant contributions to areas including computerized adaptive testing, math word problem generation, student affect detection, and automated grading systems. His recent work increasingly focuses on leveraging large language models for educational applications while maintaining rigorous scientific validation of these approaches. Best Student Paper Award at the 2024 AIED Conference (with Alexander Scarlatos) Best Paper Nominee at LAK 2021 Best Student Paper Award at IEEE Big Data 2020 NAEP Math Automated Scoring Challenge Grand Prize Winner Dr. Lan actively mentors graduate students and postdoctoral researchers, with several of his advisees receiving recognition for their work. He has secured substantial funding from the National Science Foundation, including a $90M grant for the SafeInsights project, a secure cyberinfrastructure for educational research. His research group collaborates with institutions including Worcester Polytechnic Institute, University of Pennsylvania, and Rice University. He teaches undergraduate and graduate courses including COMPSCI 240 (Reasoning under Uncertainty) and COMPSCI 590OP (Applied Numerical Optimization), with a focus on the practical application of theoretical concepts in machine learning and artificial intelligence. His educational philosophy emphasizes bridging the gap between theoretical foundations and real-world implementation in educational technology.

Daniel Frischemeierمشاهده پروفایل

استاد

• Mathematics Education
• Statistics Education
• Data Science Education
• +۵ مورد دیگر

Daniel Frischemeier is a Professor of Mathematics Didactics with a focus on Primary Education at the University of Münster's Faculty of Mathematics and Computer Science. He has established himself as a leading researcher in statistics and data science education for primary school students, with extensive contributions to educational methodology and teacher training. University of Münster (2021-present) TU Dortmund (2020-2021) University of Paderborn (2009-2020) Ludwig-Maximilians-Universität München (2017-2018) Dr. Frischemeier completed his doctoral studies at the University of Paderborn with a dissertation on statistical thinking and research using TinkerPlots software. His educational background includes graduate studies in Mathematics and undergraduate studies in Mathematics and Physics for teaching at various school levels. His research focuses on the design and testing of teaching-learning environments for primary mathematics education, particularly in the areas of data analysis, probability, and statistics. He conducts qualitative analysis of learners' cognitive processes related to the guiding principle of 'data and chance' in primary education. His work also includes the design and evaluation of teaching materials in data science and civil statistics, the use of learning videos to promote process-related skills, and the implementation of Fermi tasks and computer science education within primary mathematics lessons. Analysis of Dr. Frischemeier's recent publications reveals a strong emphasis on data literacy development in primary education, with increasing focus on the integration of digital tools and the conceptual understanding of data as models. His work bridges mathematics education with emerging fields of data science, addressing both theoretical frameworks and practical classroom applications. The research demonstrates a progression from basic statistical concepts toward more complex data modeling approaches suitable for young learners. Elected member of the International Statistical Institute (ISI) Chair of the Local Organizing Committees for IASE Satellite 2025 Conference Council-Member of the International Statistical Institute Special Edition Editor of the Statistics Education Research Journal Member of International Program Committees for major statistics education conferences Co-Leader of CERME Thematic Working Group 5 on Probability and Statistics Education Dr. Frischemeier serves in numerous editorial capacities and review roles for prominent journals in mathematics and statistics education. He leads significant research projects including 'Promoting Data Science Education for Teacher Education at the University level (DataSETUP)' and 'Data Science Education in STEAM for Civic Engagement and Social Justice from the Early Years (DataScEd4CiEn)'. His work has substantial impact on teacher education programs and curriculum development in statistics and data science for primary schools. He is actively involved in the development and leadership of the Math Center Münster (MaZ), which promotes mathematical potential for all students. His team includes numerous research assistants and doctoral candidates working on various aspects of mathematics education research, particularly focusing on data literacy and statistical reasoning in primary education contexts.

Ken Koedingerمشاهده پروفایل

استاد

• Cognitive Science
• Educational Technology
• Intelligent Tutoring Systems
• +۳ مورد دیگر

Ken Koedinger is a University Professor at Carnegie Mellon University (CMU), holding appointments in the School of Computer Science (Human-Computer Interaction Institute) and the Dietrich College of Humanities and Social Sciences (Department of Psychology). He is the co-founder of Carnegie Learning, Inc., and directs the LearnLab, now the scientific arm of CMU’s Simon Initiative. His research focuses on cognitive modeling, intelligent tutoring systems, and the science of learning. Dr. Koedinger has over 250 peer-reviewed publications and has been awarded prestigious titles such as the Hillman Professorship of Computer Science and Fellow of the Cognitive Science Society. Education: Ph.D. in Cognitive Psychology (CMU, 1990), M.S. in Computer Science (University of Wisconsin, 1986). Prior to academia, he taught in an urban high school, informing his interdisciplinary approach to education research. Research Interests: Cognitive modeling, educational technology, learning analytics, and the integration of AI into learning systems. Key projects include Cognitive Tutors, LearnLab, and the Pittsburgh Science of Learning Center. Awards: Over 30 grants from NSF, Department of Education, and private foundations, including major contributions to K-12 math education and AI-driven personalized learning. Advising: Supervised over 30 graduate students, many now leading roles in academia and industry. Current students focus on AI ethics, scalable education, and mixed-reality learning.

Kenneth Chelstمشاهده پروفایل

استاد

• Decision Analysis
• Operations Research
• K-12 Mathematics Education
• +۲ مورد دیگر

Dr. Kenneth Chelst is a Professor in the Department of Industrial and Systems Engineering at Wayne State University , where he directs the Engineering Management Program. His work bridges operations research with engineering management and K-12 mathematics education . A Rabbinic Ordination holder from Yeshiva University, he combines analytical rigor with pedagogical innovation. Educational Background: Ph.D., M.S. in Operations Research from MIT B.A. in Mathematics and Physics from Yeshiva College His research focuses on structured decision-making , OR applications in emergency services , and math curriculum development . The NSF-funded Project MINDSET ($3.3 million) and Project MEDeATe highlight his efforts to integrate OR into high school education. His From Percentage to Algebra middle school book and Ford-funded workshops have impacted hundreds of teachers. Scientific Awards: INFORMS President's Award (2011) for K-12 OR outreach Edelman Prize Laureate (2000) for Ford's OR application Multiple teaching awards from Ford Motor Company Dr. Chelst consults with Urban Science Applications Inc. and previously led the INFORMS Roundtable. His courses include Decision and Risk Analysis and Leadership Projects in Engineering Management , emphasizing corporate partnerships and immediate ROI.

• Mathematics Education
• Geometry
• Pedagogy
• +۲ مورد دیگر

Michael Weiss is a Lecturer in the Department of Mathematics at the University of Michigan. He teaches foundational courses such as Linear Algebra (MATH 217) and Explorations in Euclidean Geometry (MATH 431). His office is located in East Hall (Room 1868) at 530 Church Street, Ann Arbor, MI. Current Courses: MATH 217-004 (Linear Algebra), MATH 217-011 (Linear Algebra), MATH 431-001 (Explorations in Euclidean Geometry) Weiss’s research focuses on mathematics education, particularly on pedagogical strategies for teaching geometry and mathematical reasoning. His work explores the use of visual representations, interactive technologies, and narrative tools (e.g., comics) to enhance learning and teacher development. He emphasizes the role of theory-building in secondary geometry instruction and investigates how students translate abstract mathematical concepts into concrete reasoning. His publications highlight interdisciplinary approaches to education, integrating technology (e.g., animated stories, voice assistants) with traditional teaching methods. Keywords across his work include Mathematics Education , Geometry , Interactive Media , Visual Learning , and Teacher Training . Contact: mweiss@umich.edu

Anna Shustermanمشاهده پروفایل

استاد

• Conceptual Development
• Language and Cognition
• Numerical Cognition
• +۲ مورد دیگر

Anna Shusterman is a Professor in the Psychology Department at Wesleyan University, where she has taught and directed research in the Cognitive Development Laboratories since 2007. She co-founded and serves as co-chair of Wesleyan's College of Education Studies, established in 2020. Her educational background includes: Bachelor's degree in Neuroscience from Brown University Graduate studies and post-doctoral fellowship at Harvard University's Laboratory for Developmental Studies under Elizabeth Spelke and Susan Carey Dr. Shusterman's research centers on conceptual development in children, with a focus on the interplay between language and cognition in spatial and numerical domains. She investigates how language shapes children's understanding of numbers and space, and develops methodological approaches for translating developmental science into practical preschool classroom applications. Her work explores how young children perceive and learn about the world through simple, engaging games. Analysis of her recent publications (2019-2025) reveals consistent emphasis on numerical cognition, language acquisition, and spatial reasoning. Key themes include language's role in math development, early numeracy in diverse populations (particularly deaf and hard of hearing children), and implementation of research-based math activities in preschool settings. Her work demonstrates how language exposure in any modality supports numerical concept development and how grammatical structures influence number word acquisition. Dr. Shusterman has secured significant research funding including NSF CAREER grants and collaborative research awards. She mentors undergraduate researchers in her laboratory and actively bridges academic research with practical educational applications through her work with the College of Education Studies. She directs the Blue Lab within Wesleyan's Cognitive Development Laboratories, located in Judd Hall. The NSF-funded lab conducts studies with children under 12 from central Connecticut preschools, schools, and daycare centers, using fun games to investigate how children think about numbers, space, language, and social concepts.

Nina Berlingerمشاهده پروفایل

پژوهشگر

• Mathematics Education
• Inclusive Education
• Gifted Education
• +۳ مورد دیگر

Dr. Nina Berlinger is a researcher and educator specializing in mathematics education at the University of Münster. She is actively involved in teaching courses related to primary school mathematics education, inclusive teaching practices, and the development of mathematical talents in young children. Her work focuses on creating inclusive learning environments that cater to diverse student needs while fostering mathematical excellence. Dr. Berlinger's research interests center on inclusive mathematics education and the identification and nurturing of mathematical talents in primary school children. She has developed approaches for natural differentiation in mathematics classrooms, allowing all students to engage with challenging mathematical content at their appropriate level. Her work emphasizes creating open, substantial problem fields that provide opportunities for mathematical exploration regardless of students' prior knowledge or abilities. She investigates how spatial reasoning relates to mathematical talent development in young children and develops practical teaching strategies for educators. Her publications reveal a strong focus on inclusive mathematics education, with particular emphasis on how to design classroom settings that simultaneously support students with varying abilities while challenging mathematically talented children. She has contributed significantly to the understanding of natural differentiation in mathematics classrooms and has developed practical teaching materials like the "Mathematische Weltreise" station learning concept. Her work often bridges theory and practice, providing concrete examples like the "Wege in Manhattan" problem that demonstrate how open mathematical problems can create inclusive learning opportunities. Dr. Berlinger has received recognition through numerous publications in mathematics education journals and has presented her work at various national conferences. Her collaborative projects, particularly the "Inklusiver Mathematikunterricht" initiative, demonstrate her commitment to translating research into practical classroom applications. She actively supervises bachelor's theses and teaches multiple courses each semester, including lectures on "Lernende und Mathematik" (Learners and Mathematics) and specialized seminars on differentiating mathematics instruction for primary school children, with particular attention to mathematically talented students. She also leads seminars on promoting mathematically talented children through the MaZ (Math Center Münster) program. Dr. Berlinger is part of a research team working on inclusive mathematics education, collaborating with colleagues like Prof. Dr. Daniel Frischemeier, Prof. Dr. Marcus Nührenbörger, and Dr. Marcus Veber. Together, they have developed comprehensive approaches to inclusive mathematics teaching and teacher education.

Michelle Ellefsonمشاهده پروفایل

استاد

• Cognitive Science
• Educational Neuroscience
• Child Development
• +۶ مورد دیگر

Professor Michelle Ellefson is a Professor of Cognitive Science at the University of Cambridge's Faculty of Education, where she serves as Director of CAM-DTP and as Undergraduate Tutor for Gonville and Caius College. She convenes the INSTRUCT Research Group (Implementing New Student Thinking Resources Using Cognitive Theory) and is affiliated with multiple interdisciplinary initiatives including Cambridge Neuroscience, Cambridge Big Data, and Cambridge Language Sciences. Her educational background includes a PhD and MA in Brain and Cognitive Sciences from Southern Illinois University and a BA in Psychology, summa cum laude, from the University of Minnesota. She is a member of several professional organizations including the Psychonomic Society, Cognitive Science Society, Women in Cognitive Science, and SPARK Society. Professor Ellefson's research integrates cognition, neuroscience, child development, and education into a multi-disciplinary program aimed at improving math and science education. Her work focuses on executive functions in school achievement, children's causal reasoning about scientific phenomena, and applying cognitive principles like simplicity and desirable difficulties to classroom learning. Her research spans laboratory-based studies paired with classroom applications to understand cognitive development mechanisms and improve educational practice. Her recent publications reveal strong trends in executive function research across cultural contexts, particularly examining East-West contrasts and the relationship between executive functions and academic achievement. Her work increasingly focuses on developing and validating assessment tools like the Zoo Task for metacognitive problem-solving, and she is committed to open science practices including registered reports and pre-registration of studies. Psychonomic Society Cognitive Science Society (CogSci) Women in Cognitive Science (WiCS) SPARK Society Professor Ellefson actively supervises PhD students through the Psychology, Education & Learning Studies program and teaches cognitive psychology and educational neuroscience in the PGCE program. She emphasizes quantitative methods and R programming for data analysis, requiring doctoral students to develop strong statistical skills. Her lab follows Cambridge's inquiry-based learning model and maintains a commitment to diversity and inclusion, welcoming researchers from varied socioeconomic, national, and cultural backgrounds. The INSTRUCT Lab also focuses on open science practices, sharing data and materials through OSF and publishing preprints in Psych-Archive.

Eugene Kennedyمشاهده پروفایل

استاد

• Educational Research Methodology
• Psychometrics
• School Effectiveness
• +۳ مورد دیگر

Eugene Kennedy is a Professor in the Department of Educational Research at Louisiana State University's College of Human Sciences & Education. Holding a PhD in Educational Research Methodology from the University of South Carolina (1990), Kennedy's career spans academic research, state education departments, and technical consulting roles. His work focuses on educational effectiveness, psychometrics, and technology integration in education. Bachelor's: Sociology, Benedict College (1977) Master's: Educational Statistics & Measurement, University of Iowa (1982) PhD: Educational Research, University of South Carolina (1990) Kennedy's research interests include educational research methodology , psychometrics , school effectiveness , STEM education , data-driven decision making , and learning analytics . His recent publications demonstrate increasing focus on AI's role in education and data-driven strategies for improving educational outcomes. His academic work shows trends in educational technology integration , quantitative research methods , and STEM equity initiatives . Key themes include using data mining for educational insights, technology tools for school leadership, and innovative teaching strategies to improve student outcomes. Kennedy has participated in grants including: Co-PI for Evaluation proposal for the EBRPS American Recovery and Reinvestment Act Program (2010-2011) PI for Longitudinal Study with University of Louisiana Lafayette (2008-2009) Contact: ekennedy@lsu.edu | 221 Peabody Hall | 225-578-2193

Elizabeth Canningمشاهده پروفایل

دانشیار

• Achievement Motivation
• Social Inequality and Diversity
• Social-Psychological Interventions in Education and Organizations
• +۳ مورد دیگر

Elizabeth Canning is an Associate Professor in the Psychology Department at Washington State University (WSU), where she leads the BOLD Lab (Build. Opportunity. Learn. Develop.). Her research focuses on creating equitable and inclusive educational environments through social-psychological interventions, with specific emphasis on achievement motivation, social inequality, and organizational behavior. Ph.D. in Social Psychology from the University of Wisconsin-Madison (2016) Postdoctoral research at Indiana University’s Mind and Identity in Context Lab (2016-2019) Dr. Canning’s work investigates how institutional messages about belonging, value, and ability shape student motivation and achievement. She employs controlled experiments, randomized interventions, and longitudinal studies to mitigate disparities in STEM education, particularly for first-generation, minoritized, and stigmatized groups. Her recent publications highlight the impact of instructor mindset communication on student outcomes, strategies for reducing imposter syndrome, and the role of growth mindset cultures in organizational success. Notably, her 2024 research in CBE-Life Sciences Education demonstrated how growth mindset messaging improves first-generation student performance. Editor’s Choice, Science (2014) Dr. Canning mentors undergraduate RAs (9+ hours/week commitment) and Ph.D. students in the Experimental Psychology program. She will be on sabbatical at the Wissenschaftskolleg in Berlin during 2025-2026.

Jody Clarke-Miduraمشاهده پروفایل

استاد

• STEM Education
• Computational Thinking
• Game-Based Learning
• +۳ مورد دیگر

Dr. Jody Clarke-Midura is a Professor and Associate Dean of Graduate Studies in the Emma Eccles Jones College of Education and Human Services at Utah State University. She holds an Ed.D. from Harvard Graduate School of Education, an M.Ed. in Technology in Education, and a B.A. in English and Women’s Studies from the University of Massachusetts. Her research focuses on designing playful, technology-enhanced learning environments to foster STEM engagement and computational thinking in K-12 and early childhood education. Key areas include game-based learning, computational thinking integration, and technology-enhanced assessments. She collaborates on interdisciplinary teams and leads externally funded projects. Clarke-Midura co-directs the Playful Explorations Lab (PEL), which designs STEM learning experiences for elementary classrooms. Her work emphasizes hands-on, student-driven exploration and connects theory to classroom practice. She mentors graduate and undergraduate students, supporting their research development. Her publications address topics like formative assessments, computational thinking assessment frameworks, and the role of coding toys in early math learning. She has contributed to curriculum models integrating computer science and mathematics, and explored cultural relevance in co-design processes. Professional activities include leading graduate studies administration, advising on educational technology initiatives, and advancing inclusive pedagogical practices.