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Wilson, Cristina G.; Qian, Feifei; Jerolmack, Douglas J.; Roberts, Sonia; Ham, Jonathan; Koditschek, Daniel; Shipley, Thomas F. – Cognitive Research: Principles and Implications, 2021
How do scientists generate and weight candidate queries for hypothesis testing, and how does learning from observations or experimental data impact query selection? Field sciences offer a compelling context to ask these questions because query selection and adaptation involves consideration of the spatiotemporal arrangement of data, and therefore…
Descriptors: Hypothesis Testing, Data Collection, Information Seeking, Decision Making
Huebner, Richard A. – ProQuest LLC, 2017
The ubiquity of data in various forms has fueled the need for advanced data-mining techniques within organizations. The advent of data mining methods used to uncover hidden nuggets of information buried within large data sets has also fueled the need for determining how these unique projects can be successful. There are many challenges associated…
Descriptors: Data Analysis, Data Collection, Information Retrieval, Surveys
Baker, Ryan S. – International Journal of Artificial Intelligence in Education, 2016
The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Hypothesis Testing, Data Collection
Lansigan, Rolando R.; Moraga, Shirley D.; Batalla, Ma. Ymelda C.; Bringula, Rex P. – Education and Information Technologies, 2016
This descriptive study utilized a validated questionnaire that gathered data from freshmen of two different school years. Demographic profile, marketers (i.e., source of information of students about the school), influencers (i.e., significant others that persuaded them to enroll in the school), level of school choice, and level of consideration…
Descriptors: Foreign Countries, College Choice, Social Media, College Freshmen
Regional Educational Laboratory Mid-Atlantic, 2013
This event focused on the What Works Clearinghouse practice guide, "Using Student Achievement Data to Support Instructional Decision Making" (ED506645). During the event, the presenter, Sharnell Jackson, led school data teams in activities involving analysis of their own student data. This Q&A addressed the questions participants had…
Descriptors: Academic Achievement, Decision Making, Data Analysis, Feedback (Response)
Killen, Catherine P. – European Journal of Engineering Education, 2015
This paper outlines a novel approach to engineering education research that provides three dimensions of learning through an experiential class activity. A simulated decision activity brought current research into the classroom, explored the effect of experiential activity on learning outcomes and contributed to the research on innovation decision…
Descriptors: Engineering Education, Educational Innovation, Educational Research, Experiential Learning
Nichols, Timothy; Ailts, Jacob; Chang, Kuo-Liang – Honors in Practice, 2016
This study gathered, analyzed, and compared perspectives of students who were honors-eligible but never began the program, students who began in honors and discontinued their enrollment, and those who were persisting in honors. Broadly speaking (and not surprisingly), the responses of students persisting in honors reflected the most positive…
Descriptors: Higher Education, College Students, School Holding Power, Honors Curriculum
Creighton, Theodore B. – 2001
This book focuses on the relevance of statistics in the day-to-day lives of principals and teachers. The step-by-step guide to using existing school data can help school leaders make more appropriate and effective decisions. The information is presented with easy-to-follow instructions, illustrations, and pertinent examples. The chapters are: (1)…
Descriptors: Analysis of Variance, Correlation, Data Analysis, Data Collection

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