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Ammar, Salwa; Kim, Min Jung; Masoumi, Amir H.; Tomoiaga, Alin – Decision Sciences Journal of Innovative Education, 2023
Over the past few years, academics have undertaken initiatives to bridge the gap between theory and practice in the ever-growing field of business analytics, including implementing real-life student projects in all shapes and forms. Every year since 2015, Manhattan College has invited student teams from across North America and elsewhere in the…
Descriptors: Business, Data Analysis, Business Administration Education, Intercollegiate Cooperation
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Kuroki, Masanori – Journal of Economic Education, 2023
As vast amounts of data have become available in business in recent years, the demand for data scientists has been rising. The author of this article provides a tutorial on how one entry-level machine learning competition from Kaggle, an online community for data scientists, can be integrated into an undergraduate econometrics course as an…
Descriptors: Statistics Education, Teaching Methods, Competition, Prediction
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Bulut, Okan; Yavuz, Hatice Cigdem – International Journal of Assessment Tools in Education, 2019
Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDM offers promising solutions to complex educational problems. Given the rapid increase in the availability of big data in education and software…
Descriptors: Data Analysis, Educational Research, Educational Researchers, Computer Software
Andrew Gelman; Daniel Lee; Jiqiang Guo – Journal of Educational and Behavioral Statistics, 2015
Stan is a free and open-source C++ program that performs Bayesian inference or optimization for arbitrary user-specified models and can be called from the command line, R, Python, Matlab, or Julia and has great promise for fitting large and complex statistical models in many areas of application. We discuss Stan from users' and developers'…
Descriptors: Programming Languages, Bayesian Statistics, Inferences, Monte Carlo Methods
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Parkavi, A.; Lakshmi, K.; Srinivasa, K. G. – Educational Research and Reviews, 2017
Data analysis techniques can be used to analyze the pattern of data in different fields. Based on the analysis' results, it is recommended that suggestions be provided to decision making authorities. The data mining techniques can be used in educational domain to improve the outcome of the educational sectors. The authors carried out this research…
Descriptors: Data Analysis, Educational Research, Goodness of Fit, Decision Making
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Akar, Sacide Guzin Mazman; Altun, Arif – Contemporary Educational Technology, 2017
The purpose of this study is to investigate and conceptualize the ranks of importance of social cognitive variables on university students' computer programming performances. Spatial ability, working memory, self-efficacy, gender, prior knowledge and the universities students attend were taken as variables to be analyzed. The study has been…
Descriptors: Individual Differences, Learning Processes, Programming, Self Efficacy
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Van Horne, Sam; Russell, Jae-eun; Schuh, Kathy L. – Educational Technology Research and Development, 2016
Researchers have more often examined whether students prefer using an e-textbook over a paper textbook or whether e-textbooks provide a better resource for learning than paper textbooks, but students' adoption of mark-up tools has remained relatively unexamined. Drawing on the concept of Innovation Diffusion Theory, we used educational data mining…
Descriptors: Programming Languages, Hypermedia, Electronic Publishing, Textbooks
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Bringula, Rex P.; Manabat, Geecee Maybelline A.; Tolentino, Miguel Angelo A.; Torres, Edmon L. – World Journal of Education, 2012
This descriptive study determined which of the sources of errors would predict the errors committed by novice Java programmers. Descriptive statistics revealed that the respondents perceived that they committed the identified eighteen errors infrequently. Thought error was perceived to be the main source of error during the laboratory programming…
Descriptors: Error Patterns, Programming, Programming Languages, Predictor Variables
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Ghani, Erlane K.; Jusoff, Kamaruzaman – International Education Studies, 2009
An extensive literature has emerged in the past decade that examined financial reporting in a digital environment. This study extends this literature by examining the factors that may influence the preference of a digital presentation format. Using questionnaire design, this study examines whether public accounting practitioners' work experience…
Descriptors: Foreign Countries, Accounting, Work Experience, Hypermedia