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Yi, Zhihui; Schreiber, James B.; Paliliunas, Dana; Barron, Becky F.; Dixon, Mark R. – Journal of Behavioral Education, 2021
The recent commentary by Beaujean and Farmer (2020) on the original paper by Dixon et al. (2019) serves a cautionary tale of selective p-values, the law of small N sizes, and the type-II error. We believe these authors have crafted a somewhat questionable argument in which only 57% of the original Dixon et al. data were re-analyzed, based on a…
Descriptors: Research Problems, Data Analysis, Statistical Analysis, Probability
Kuby, Candace R.; Rowsell, Jennifer – International Studies in Sociology of Education, 2022
This article conceptualizes the notion of magic(al)ing in relation to post-pandemic ways of thinking about data production and analyses. Revisiting old data produced pre-COVID-19 and engaging with new data produced during COVID-19, we consider the possibilities and potential of magic(al)ing as a theoretical concept. We think with several ideas…
Descriptors: COVID-19, Pandemics, Data Analysis, Philosophy
Complete College America, 2023
In this position paper, the authors lay out the imperative for equitable artificial intelligence (AI), highlighting the essential role of access-oriented institutions and calling on technology companies (both large and small), foundations, and local, state, and federal regulators to consult with the newly convened Complete College America Council…
Descriptors: Artificial Intelligence, Computer Uses in Education, Higher Education, Graduation
Hammersley, Martyn – International Journal of Social Research Methodology, 2021
This paper responds to some recent discussions in the Journal about how interview data can be used. While recognising the value of detailed analysis of the discourse employed in interviews to identify its formal features, it is argued that such analysis is not essential for all the purposes for which interview data can be employed in social…
Descriptors: Interviews, Social Science Research, Language Usage, Discourse Analysis
Leighton, Jacqueline P. – Applied Measurement in Education, 2021
The objective of this paper is to comment on the think-aloud methods presented in the three papers included in this special issue. The commentary offered stems from the author's own psychological investigations of unobservable information processes and the conditions under which the most defensible claims can be advanced. The structure of this…
Descriptors: Protocol Analysis, Data Collection, Test Construction, Test Validity
Regan, Daniel – New England Journal of Higher Education, 2021
A gap exists between the ability to gauge the success of institutions by deploying a relatively simple set of measures typically based upon the federal cohort, versus the ability to monitor the successful (or unsuccessful) progression of the varied students who move through them. Daniel Regan questions which matters more. To gauge the health of an…
Descriptors: Data Use, Decision Making, Academic Achievement, College Students
Esther Ulitzsch; Qiwei He; Steffi Pohl – Grantee Submission, 2024
This is an editorial for a special issue "Innovations in Exploring Sequential Process Data" in the journal Zeitschrift für Psychologie. Process data refer to log files generated by human-computer interactive items. They document the entire process, including keystrokes, mouse clicks as well as the associated time stamps, performed by a…
Descriptors: Educational Innovation, Man Machine Systems, Educational Technology, Computer Assisted Testing
Bernard, Taryn – Journal of Student Affairs in Africa, 2021
When writing about transformation in higher education (HE) in South Africa, it is quite popular to mention the fall of apartheid, and perhaps also 1994, as a starting point for significant change. I, myself, have made this mistake (see Bernard, 2015). However, the recent #FeesMustFall protests highlighted that many approaches to transformation…
Descriptors: Educational Environment, Foreign Countries, Higher Education, Educational Change
Cui, Zhongmin – Educational Measurement: Issues and Practice, 2021
Commonly used machine learning applications seem to relate to big data. This article provides a gentle review of machine learning and shows why machine learning can be applied to small data too. An example of applying machine learning to screen irregularity reports is presented. In the example, the support vector machine and multinomial naïve…
Descriptors: Artificial Intelligence, Man Machine Systems, Data, Bayesian Statistics
Perrone, Frank; Young, Michelle D.; Fuller, Edward J. – Educational Researcher, 2022
In this policy forum commentary, we call for improved national and state-level data collection and access relevant to the principal pipeline. We focus specifically on how access to quality data can inform, has informed, and is critical to policy and practice across three segments of the principal pipeline--principal preparation, licensure, and…
Descriptors: Principals, Administrator Education, Educational Policy, Educational Legislation
The Vulnerable Insider: Navigating Power, Positionality and Being in Educational Technology Research
Tshuma, Nompilo – Learning, Media and Technology, 2021
This article reflects on the tensions I encountered as an insider researcher during a qualitative study exploring academics' integration of educational technology in a South African higher education institution. While critical qualitative approaches acknowledge research participants' vulnerability to the researcher's interpretation and…
Descriptors: Educational Technology, Technology Integration, Educational Researchers, Doctoral Students