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Atkinson, Joshua D.; Dorr, Matthew; Pedasanaganti, Vamsi; Sharma, Shudipta – Journal of Ethnographic & Qualitative Research, 2023
The framework of cyber-archaeology was developed by Jones (1997, 2003) and later modified by Zimbra et al. (2010) to examine online networks and virtual communities. Since the modification, the method has fallen out of favor and is no longer utilized by qualitative researchers. To rebuild the method for qualitative research, we engaged in four…
Descriptors: Qualitative Research, Interdisciplinary Approach, Archaeology, Computer Science
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Ozlem Oktay; Ilknur Reisoglu; Seyda Gul; Dilek Teke; Mustafa Sozbilir; Ilayda Gunes; Rumeysa Yildiz; Gulsah Atila; Aysegul Yazar; Lauri Malmi; Päivi Kinnunen; Jarkko Lampiselkä; Arja Kaasinen – Scandinavian Journal of Educational Research, 2025
The aim of this study is to compare the master's (MA) theses in Türkiye (TR) and Finland (FIN) published between 2015-2019. A total of 765 theses were analysed in terms of year, discipline, methodological approach, research method, didactic foci, data collection tool, target group, and sample size. The results showed that FIN theses grounded on…
Descriptors: Foreign Countries, Masters Theses, STEM Education, Intellectual Disciplines
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Seliem El-Sayed; Filip Paspalj – Research Ethics, 2024
Recital 33 GDPR has often been interpreted as referring to 'broad consent'. This version of informed consent was intended to allow data subjects to provide their consent for certain areas of research, or parts of research projects, conditional to the research being in line with 'recognised ethical standards'. In this article, we argue that broad…
Descriptors: Ethics, Social Science Research, Standards, Data Analysis
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Renu, N.; Sunil, K. – Higher Education for the Future, 2023
Integration of computational data science (CDS) into the university curriculum offers several advantages for students, faculty and the institution. This article discusses the benefits to students of introducing CDS into the university curriculum with a focus on developing skills in cheminformatics, data analysis, structure--activity relationships,…
Descriptors: Data Science, Higher Education, College Students, Skill Development
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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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Tapprich, William E.; Reichart, Letitia; Simon, Dawn M.; Duncan, Garry; McClung, William; Grandgenett, Neal; Pauley, Mark A. – Biochemistry and Molecular Biology Education, 2021
The lack of an instructional definition of bioinformatics delays its effective integration into biology coursework. Using an iterative process, our team of biologists, a mathematician/computer scientist, and a bioinformatician together with an educational evaluation and assessment specialist, developed an instructional definition of the…
Descriptors: Scoring Rubrics, Definitions, Genetics, Biology
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Okhee Lee; Scott Grapin – Journal of Research in Science Teaching, 2025
We propose a conceptual framework for STEM education that is centered around justice for minoritized groups. Justice-centered STEM education engages all students in multiple STEM subjects, including data science and computer science, to explain and design solutions to societal challenges disproportionately impacting minoritized groups. We…
Descriptors: Social Justice, STEM Education, Bilingual Students, Multilingualism
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Grapin, Scott E.; Haas, Alison; McCoy, N'Dyah; Lee, Okhee – Journal of Science Teacher Education, 2023
When pressing societal challenges (e.g., COVID-19, access to clean water) are sidelined in science classrooms, science education fails to leverage the knowledge and experiences of minoritized students in school, thus reproducing injustices in society. Our conceptual framework for "justice-centered STEM education" engages all students in…
Descriptors: STEM Education, Multilingualism, Inquiry, Preservice Teachers
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Kjelvik, Melissa K.; Schultheis, Elizabeth H. – CBE - Life Sciences Education, 2019
Data are becoming increasingly important in science and society, and thus data literacy is a vital asset to students as they prepare for careers in and outside science, technology, engineering, and mathematics and go on to lead productive lives. In this paper, we discuss why the strongest learning experiences surrounding data literacy may arise…
Descriptors: Data Use, Scientific Research, Information Literacy, STEM Education
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Ndudi O. Ezeamuzie; Jessica S. C. Leung; Dennis C. L. Fung; Mercy N. Ezeamuzie – Journal of Computer Assisted Learning, 2024
Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational…
Descriptors: Educational Policy, Predictor Variables, Computation, Thinking Skills
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Lee, Okhee; Campbell, Todd – Journal of Science Teacher Education, 2020
The COVID-19 pandemic is a historic global event that has extended to all parts of society and shaken the core of what we know and how we live. During this pandemic, the work of STEM professionals has taken center stage. Through our close observations of how the events of the pandemic have been unfolding across the globe, we propose an…
Descriptors: COVID-19, Pandemics, Science Teachers, Science Education
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Selwyn, Neil; Gaševic, Dragan – Teaching in Higher Education, 2020
A common recommendation in critiques of datafication in education is for greater conversation between the two sides of the (critical) divide -- what might be characterised as sceptical social scientists and (supposedly) more technically-minded and enthusiastic data scientists. This article takes the form of a dialogue between two academics…
Descriptors: Criticism, Data Analysis, Higher Education, Dialogs (Language)
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Güven, Ismail; Gulbahar, Yasemin – Social Studies, 2020
Computational Thinking (CT) has recently been addressed as one of the key skills for the twenty-first century. Integrating CT into different subject areas of K-12 education is also now widely accepted to improve the quality of instruction. In that sense, it is important to enable educators and researchers to recognize how to integrate…
Descriptors: Thinking Skills, Computer Science, Social Studies, 21st Century Skills
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Ilic, Ulas; Haseski, Halil Ibrahim; Tugtekin, Ufuk – Contemporary Educational Technology, 2018
The current study aimed to review studies on computational thinking (CT) indexed in Web of Science (WOS) and ERIC databases. A thorough search in electronic databases revealed 96 studies on computational thinking which were published between 2006 and 2016. Studies were exposed to a quantitative content analysis through using an article control…
Descriptors: Trend Analysis, Educational Trends, Periodicals, Databases
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Grant, Robert – Statistics Education Research Journal, 2017
Statistical literacy, the ability to understand and make use of statistical information including methods, has particular relevance in the age of data science, when complex analyses are undertaken by teams from diverse backgrounds. Not only is it essential to communicate to the consumers of information but also within the team. Writing from the…
Descriptors: Data, Statistics, Numeracy, Artificial Intelligence
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