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Yuan, Shuaihang – ProQuest LLC, 2023
Recently, with the advancement in 2D imaging techniques and 3D visual sensors such as LiDAR, RGB-D cameras, etc. The use of 2D and 3D data is ubiquitous in various fields like autonomous driving, AR, and VR. Therefore, we are faced with an ever-increasing demand for approaches toward the automatic processing and analysis of data from multiple…
Descriptors: Computer Simulation, Geometry, Artificial Intelligence, Data Analysis
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Nehyba, Jan; Štefánik, Michal – Education and Information Technologies, 2023
Social sciences expose many cognitively complex, highly qualified, or fuzzy problems, whose resolution relies primarily on expert judgement rather than automated systems. One of such instances that we study in this work is a reflection analysis in the writings of student teachers. We share a hands-on experience on how these challenges can be…
Descriptors: Models, Language, Reflection, Writing (Composition)
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Gao, Lei; Guo, Miao – Biochemistry and Molecular Biology Education, 2023
With rapid development of sequencing technology and the continuous accumulation of biological big data, people who are capable of using bioinformatic skills to analyze omics data and work out biological problems are urgently needed in the workforce, which highlights the importance of developing bioinformatics skills early in the undergraduate…
Descriptors: Undergraduate Students, Student Research, Student Experience, Biology
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Kearney, Christopher A.; Childs, Joshua – Improving Schools, 2023
School attendance and absenteeism are critical targets of educational policies and practices that often depend heavily on aggregated attendance/absenteeism data. School attendance/absenteeism data in aggregated form, in addition to having suspect quality and utility, minimizes individual student variation, distorts detailed and multilevel…
Descriptors: Data Analysis, Attendance, Educational Policy, Causal Models
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Xia, Xiaona – Interactive Learning Environments, 2023
Learning interaction activities are the key part of tracking and evaluating learning behaviors, that plays an important role in data-driven autonomous learning and optimized learning in interactive learning environments. In this study, a big data set of learning behaviors with multiple learning periods is selected. According to the instance…
Descriptors: Behavior, Learning Processes, Electronic Learning, Algorithms
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Pule, Heather – Journal of Adolescent & Adult Literacy, 2023
While culturally responsive texts have become more common in teacher education, too often, preservice teachers (PTs) are not asked to examine how to use these books pedagogically. To address this issue, in a young adult (YA) literature course, the Framework for Culturally and Historically Responsive Literacy (HRL) (Muhammad, 2000)…
Descriptors: Adolescent Literature, Preservice Teachers, Literacy, Data Analysis
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McKinney, Earl, Jr.; Niese, Bethany; Bhatia, Mantek Singh – Journal of Information Systems Education, 2023
Active learning pedagogy has many documented benefits, and while several positive examples of its recent use in STEM classes have led to better performance, greater diversity, more equity, and improved retention of underrepresented student populations, more research in IS and IT classrooms is needed. Most active learning exercises are in a…
Descriptors: Active Learning, Audience Response Systems, Teaching Methods, Data Analysis
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Wang, Wei; Zhao, Yongyong; Wu, Yenchun Jim; Goh, Mark – International Journal of Science Education, Part B: Communication and Public Engagement, 2023
This study analyzed the influence of rhetoric in the endorsement text on the willingness of the crowd to participate in citizen science projects. Four categories of endorsers were studied: professors, students, industrial researchers, and amateur researchers. Using 1243 endorsement texts from 543 citizen science projects as the corpus, the effects…
Descriptors: Citizen Participation, Science Education, Rhetoric, Scientific Research
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Beechey, Timothy – Journal of Speech, Language, and Hearing Research, 2023
Purpose: This article provides a tutorial introduction to ordinal pattern analysis, a statistical analysis method designed to quantify the extent to which hypotheses of relative change across experimental conditions match observed data at the level of individuals. This method may be a useful addition to familiar parametric statistical methods…
Descriptors: Hypothesis Testing, Multivariate Analysis, Data Analysis, Statistical Inference
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Bignami-Van Assche, Simona; Boulet, Virginie; Simard, Charles-Olivier – Sociological Methods & Research, 2023
How household-level data from censuses and surveys are analyzed to study household structure is an issue that has received little attention. The present study proposes a new methodological approach to address this gap. Specifically, we introduce the idea of the household configuration as a mathematical representation of observations from the…
Descriptors: Family Structure, Census Figures, Surveys, Indigenous Populations
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Fitzgerald, Sarah Rose; Reznik-Zellen, Rebecca; Berube, Suenita; Fischietto, Cai – College & Research Libraries, 2023
The purpose of this study is to investigate what semiotic analysis can reveal about how welcoming and inclusive a science library space is for patrons. A space was examined in terms of its messaging to patrons of various genders, abilities, races, ethnicities, nationalities, and disciplines. Findings are presented about the space's messaging…
Descriptors: Research Libraries, Sciences, Semiotics, Inclusion
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Thomson, Rachel; Owens, Rachael; Redman, Peter; Webb, Rebecca – Child Care in Practice, 2023
What do we do with emotion in biographical research: is it an end in itself, a symptom to be explained, a thread to be pulled? This paper presents an experiment in methodology within a field of biographical methods that involved revisiting a single qualitative interview after the elapse of thirty years. The interview with 22 year old Stacey was…
Descriptors: Research Methodology, Psychological Patterns, Qualitative Research, Interviews
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Tackett, Maria – Journal of Statistics and Data Science Education, 2023
As data have become more prevalent in academia, industry, and daily life, it is imperative that undergraduate students are equipped with the skills needed to analyze data in the modern environment. In recent years there has been a lot of work innovating introductory statistics courses and developing introductory data science courses; however,…
Descriptors: Educational Change, Undergraduate Students, Regression (Statistics), Statistics Education
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Maqsood, Rabia; Ceravolo, Paolo; Ahmad, Muhammad; Sarfraz, Muhammad Shahzad – International Journal of Educational Technology in Higher Education, 2023
The heterogeneous data acquired by educational institutes about students' careers (e.g., performance scores, course preferences, attendance record, demographics, etc.) has been a source of investigation for Educational Data Mining (EDM) researchers for over two decades. EDM researchers have primarily focused on course-specific data analyses of…
Descriptors: Foreign Countries, Computer Science, Undergraduate Students, Private Colleges
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Ismail, Azlan; Mutalib, Sofianita; Haron, Haryani – Education and Information Technologies, 2023
This article discusses the key elements of the Data Science Technology course offered to postgraduate students enrolled in the Master of Data Science program. This course complements the existing curriculum by providing the skills to handle the Big Data platform and tools, in addition to data science activities. We tackle the discussion about this…
Descriptors: Data Science, Graduate Study, Masters Programs, Graduate Students
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