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Ward, Jason K.; Comer, Unoma; Stone, Suki – Interchange: A Quarterly Review of Education, 2018
This article presents the use of the qualitative research method and the challenges that this form of research imposes along with the increasingly systematic reluctance experienced by doctoral students and their chairs. Increasingly, doctoral students are opting for the qualitative approach over that of the traditional quantitative methodology.…
Descriptors: Qualitative Research, Graduate Students, Student Research, Data Collection
Bharara, Sanyam; Sabitha, Sai; Bansal, Abhay – Education and Information Technologies, 2018
Learning Analytics (LA) is an emerging field in which sophisticated analytic tools are used to improve learning and education. It draws from, and is closely tied to, a series of other fields of study like business intelligence, web analytics, academic analytics, educational data mining, and action analytics. The main objective of this research…
Descriptors: Data Collection, Data Analysis, Correlation, Academic Achievement
Snyder, Johnny – Information Systems Education Journal, 2019
Quantitative decision making (management science, business statistics) textbooks rarely address data cleansing issues, rather, these textbooks come with neat, clean, well-formatted data sets for the student to perform analysis on. However, with a majority of the data analyst's time spent on gathering, cleaning, and pre-conditioning data, students…
Descriptors: Data Analysis, Error Patterns, Data Collection, Spreadsheets
Prinsloo, Paul – British Journal of Educational Technology, 2019
Data--their collection, analysis and use--have always been part of education, used to inform policy, strategy, operations, resource allocation, and, in the past, teaching and learning. Recently, with the emergence of learning analytics, the collection, measurement, analysis and use of student data have become an increasingly important research…
Descriptors: Learning Analytics, Data Collection, Data Analysis, Measurement
Nicholas Raikes – Research Matters, 2019
Big international assessment organisations like Cambridge Assessment have long held considerable amounts of data. When text is produced digitally, we can do more with it. Surprisingly to many, there have been examples of automatic scoring of extended writing for around 20 years, though what works well in one context may not be applicable in all…
Descriptors: Data Collection, Data Analysis, Evaluation, Technology Uses in Education
Skhvediani, Angi; Sosnovskikh, Sergey; Rudskaia, Irina; Kudryavtseva, Tatiana – Journal of Education for Business, 2022
The development of digital technologies has created a market need for specialists working with the big data that is necessary for making management decisions. This study aims to identify the skills structure of the data analyst profession (DAP) in Russia. The authors used a program code written in Python to examine relevant vacancies extracted…
Descriptors: Data Analysis, Employment Qualifications, Higher Education, Curriculum Development
Gurney, Laura, Ed.; Wang, Yi, Ed.; Barnard, Roger, Ed. – Routledge Research in Education, 2022
The book provides a grounded, narrative exploration of contemporary qualitative PhD research in the fields of language education and applied linguistics. The chapters are authored by current and former PhD candidates studying in New Zealand, with commentaries from international experts in the field. The book contains ten chapters in addition to…
Descriptors: Doctoral Students, Student Research, Applied Linguistics, Second Language Instruction
Gómez-Torres, Emilse – Statistics Education Research Journal, 2021
This paper describes the evolution of "recognition of need for data" and "strategical thinking", two types of thinking identified by Wild and Pfannkuch in their Framework for Statistical Thinking in Empirical Enquiry, as well as its relevance for math teacher professional development. The research was carried out with ten…
Descriptors: Thinking Skills, Mathematics Teachers, Secondary School Teachers, Data Analysis
Region 9 Comprehensive Center, 2021
The COVID-19 pandemic has created an unprecedented challenge for state, district, and school leaders across the country. Whether states and districts mandate or choose an in-person or remote model or a hybrid model, which includes some aspect of virtual learning, ensuring that vulnerable students and teachers have a remote learning option has…
Descriptors: Distance Education, Blended Learning, Educational Quality, Data Collection
Yildiz, Gizem; Yildirim, Abdurrahman; Akça, Bedreddin Ali; Kök, Ayse; Özer, Açelya; Karatas, Serçin – International Review of Research in Open and Distributed Learning, 2020
A total of 1023 selected articles published in 2016-2019 related to mobile learning were examined and classified according to the categories in this research: 40% of these articles used quantitative approaches, 18% of them used mixed, and 13% of them were literature reviews. The published studies were analyzed according to research model, sample…
Descriptors: Educational Trends, Educational Research, Electronic Learning, Handheld Devices
Pistilli, Matthew D.; Heileman, Gregory L. – New Directions for Higher Education, 2017
This chapter provides information on how the promise of analytics can be realized in gateway courses through a combination of good data science and the thoughtful application of outcomes to teaching and learning improvement efforts--especially with and among instructors.
Descriptors: Data Collection, Data Analysis, Introductory Courses, Outcomes of Education
Brion-Meisels, Gretchen; O'Neil, Eliza; Bishop, Sarah – Equity Assistance Center Region II, Intercultural Development Research Association, 2022
Before developing a school- and community-wide work plan around preventing bullying and harassment, school administrators should employ data collection tools to determine their specific areas of focus. Successful bullying prevention efforts must be driven by local data and rooted in research on effective practices. These policies must undergo…
Descriptors: Bullying, Prevention, Antisocial Behavior, Educational Practices
Cannistrà, Marta; Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, Anna Maria – Studies in Higher Education, 2022
This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…
Descriptors: Dropouts, Potential Dropouts, Dropout Prevention, Dropout Characteristics
Fawcett, Darcy – set: Research Information for Teachers, 2019
This Assessment News article introduces readers to a statistical approach to making sense of student assessment data in order to help teachers understand whether or not changes in practice have made a difference to learning. It Worked! is the brainchild of Darcy Fawcett, HoD Science at Gisborne Boys' High School, and Across-School Teacher for the…
Descriptors: Data Analysis, Data Use, Evidence Based Practice, Communities of Practice
McChesney, Katrina; Aldridge, Jill – International Journal of Research & Method in Education, 2019
A recurring debate in mixed methods research involves the relationship between research methods and research paradigms. Whereas some scholars appear to assume that qualitative and quantitative research methods each necessarily belong with particular research paradigms, others have called for greater flexibility and have taken a variety of stances…
Descriptors: Mixed Methods Research, Models, Research Design, Data Collection