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Anthony S. DiStefano; Joshua S. Yang – Field Methods, 2024
Despite recent methodological advances in saturation, guidelines for its estimation in more complex research designs--such as ethnographic studies--have been lacking. We present an accessible, step-by-step approach to empirical assessment of data saturation, tested on a moderately sized ethnographic study with 109 combined direct observations and…
Descriptors: Sample Size, Ethnography, Research Methodology, Research Design
Sales, Adam C.; Prihar, Ethan B.; Gagnon-Bartsch, Johann A.; Heffernan, Neil T. – Journal of Educational Data Mining, 2023
Randomized A/B tests within online learning platforms represent an exciting direction in learning sciences. With minimal assumptions, they allow causal effect estimation without confounding bias and exact statistical inference even in small samples. However, often experimental samples and/or treatment effects are small, A/B tests are underpowered,…
Descriptors: Data Use, Research Methodology, Randomized Controlled Trials, Educational Technology
Worsley, Marcelo; Martinez-Maldonado, Roberto; D'Angelo, Cynthia – Journal of Learning Analytics, 2021
Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12…
Descriptors: Learning Analytics, Artificial Intelligence, Data Collection, Statistical Inference
Colver, Mitchell – New Directions for Institutional Research, 2019
As we become increasingly acquainted with the rich opportunities that analytics systems can provide, there is a commensurate need to consider the extent to which analytics tools are effectively integrated, with proper training, into the day-to-day functioning of higher education professionals. This chapter explores the extent to which predictive…
Descriptors: Data Collection, Data Analysis, Educational Research, Higher Education
Fryer, Luke K.; Nakao, Kaori – Frontline Learning Research, 2020
Self-report is a fundamental research tool for the social sciences. Despite quantitative surveys being the workhorses of the self-report stable, few researchers question their format--often blindly using some form of Labelled Categorical Scale (Likert-type). This study presents a brief review of the current literature examining the efficacy of…
Descriptors: Measurement Techniques, Research Methodology, Surveys, Online Surveys
Hutner, Todd L.; Markman, Arthur B. – Science Education, 2016
Research on science teacher cognition is important as findings from this research can be used to improve teacher training, leading to improved classroom practice. Previous research has often relied on two underlying assumptions: Cognition is an individual process, and these processes are detailed and introspective. In this paper, we put forth a…
Descriptors: Science Teachers, Science Instruction, Schemata (Cognition), Models
Lindsay, Jim; Wan, Yinmei; Berg-Jacobson, Alexander; Walston, Jill; Redford, Jeremy – Regional Educational Laboratory Midwest, 2016
Every year the U.S. Department of Education reports for each state in the country the grade levels, subject areas, and geographic areas that have experienced teacher shortages (U.S. Department of Education, Office of Postsecondary Education, 2015). A teacher shortage occurs when the number of teachers available in a specific grade, subject matter…
Descriptors: Teacher Supply and Demand, Teacher Shortage, State Legislation, Surveys
Smith, Marlene A.; Kellogg, Deborah L. – Decision Sciences Journal of Innovative Education, 2015
This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…
Descriptors: Group Activities, Assignments, Cooperative Learning, Individual Activities
Lei, Wu; Qing, Fang; Zhou, Jin – International Journal of Distance Education Technologies, 2016
There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…
Descriptors: Causal Models, Attribution Theory, Correlation, Evaluation Methods
Tekin, Ahmet – Eurasian Journal of Educational Research, 2014
Problem Statement: There has recently been interest in educational databases containing a variety of valuable but sometimes hidden data that can be used to help less successful students to improve their academic performance. The extraction of hidden information from these databases often implements aspects of the educational data mining (EDM)…
Descriptors: Foreign Countries, Prediction, Grade Point Average, Undergraduate Students
Lawson, Anton E. – Science Education Review, 2008
We should dispense with use of the confusing term "null hypothesis" in educational research reports. To explain why the term should be dropped, the nature of, and relationship between, scientific and statistical hypothesis testing is clarified by explication of (a) the scientific reasoning used by Gregor Mendel in testing specific…
Descriptors: Hypothesis Testing, Educational Research, Statistical Analysis, Prediction
Jelicic, Helena; Phelps, Erin; Lerner, Richard M. – Journal of Youth and Adolescence, 2010
The study of adolescent development rests on methodologically appropriate collection and interpretation of longitudinal data. While all longitudinal studies of adolescent development involve missing data, the methods to treat missingness that have been recommended most often focus on missing data from cross-sectional studies. The problems of…
Descriptors: Adolescent Development, Family Structure, Geographic Regions, Data Collection
Baker, Ryan S. J. D.; Yacef, Kalina – Journal of Educational Data Mining, 2009
We review the history and current trends in the field of Educational Data Mining (EDM). We consider the methodological profile of research in the early years of EDM, compared to in 2008 and 2009, and discuss trends and shifts in the research conducted by this community. In particular, we discuss the increased emphasis on prediction, the emergence…
Descriptors: Trend Analysis, Educational History, Educational Research, Research Methodology

Robbins, Gerold E. – Journal of Research in Personality, 1975
Subjects were assigned the task of forming an impression of another person with information being gathered from two conflicting sources. (Editor)
Descriptors: Data Collection, Dogmatism, Flow Charts, Personality Studies

Van Acker, Richard; And Others – Journal of Special Education Technology, 1991
Twelve trained observers were randomly assigned to one of two methods of data collection in scoring teacher-student interactions. Results indicated no overall difference in observer accuracy between momentary time sampling and continuous data collection when scoring behaviors that differed along the dimensions of frequency and predictability.…
Descriptors: Classroom Communication, Classroom Observation Techniques, Data Collection, Interaction
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