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Lafuente, Deborah; Cohen, Brenda; Fiorini, Guillermo; Garci´a, Agusti´n Alejo; Bringas, Mauro; Morzan, Ezequiel; Onna, Diego – Journal of Chemical Education, 2021
Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks…
Descriptors: Undergraduate Students, Chemistry, Electronic Learning, Artificial Intelligence
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Chen Zhong; J. B. Kim – Journal of Information Systems Education, 2024
Data Analytics has emerged as an essential skill for business students, and several tools are available to support their learning in this area. Due to the students' lack of programming skills and the perceived complexity of R, many business analytics courses employ no-code analytical software like IBM SPSS Modeler. Nonetheless, generative…
Descriptors: Business Education, Regression (Statistics), Programming, Artificial Intelligence
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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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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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Simkin, Mark; Stiver, Debra – Journal of Education for Business, 2016
Allowing students to grade their own homework promises many advantages. But can students perform such grading tasks honestly and accurately? Also, do such assessments vary by gender? To answer these questions, the authors analyzed the homework scores of 266 students in seven introductory programming classes. The statistical results were favorable…
Descriptors: Homework, Self Evaluation (Individuals), Student Evaluation, Gender Differences
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Maguire, Phil; Maguire, Rebecca; Kelly, Robert – Computer Science Education, 2017
We report on an intervention in which informal programming labs were switched to a weekly machine-evaluated test for a second year Data Structures and Algorithms module. Using the online HackerRank system, we investigated whether greater constructive alignment between course content and the exam would result in lower failure rates. After…
Descriptors: Programming, Computer Science Education, Teaching Methods, Test Scoring Machines
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Wong, Wang-chan – Information Systems Education Journal, 2015
In this paper, the author reports the results of an empirical study on the relationship between a student's programming experience and their success in a traditional Systems Analysis and Design (SA&D) class where technical skills such as dataflow analysis and entity relationship data modeling are covered. While it is possible to teach these…
Descriptors: Programming, Information Systems, Systems Analysis, Design
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Maaliw, Renato R. III; Ballera, Melvin A. – International Association for Development of the Information Society, 2017
The usage of data mining has dramatically increased over the past few years and the education sector is leveraging this field in order to analyze and gain intuitive knowledge in terms of the vast accumulated data within its confines. The primary objective of this study is to compare the results of different classification techniques such as Naïve…
Descriptors: Classification, Cognitive Style, Electronic Learning, Decision Making
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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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Erhardt, Robert J.; Shuman, Michael P. – Journal of Statistics Education, 2015
At Wake Forest University, a student who is blind enrolled in a second course in statistics. The course covered simple and multiple regression, model diagnostics, model selection, data visualization, and elementary logistic regression. These topics required that the student both interpret and produce three sets of materials: mathematical writing,…
Descriptors: Blindness, Statistics, College Mathematics, College Students
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Benakli, Nadia; Kostadinov, Boyan; Satyanarayana, Ashwin; Singh, Satyanand – International Journal of Mathematical Education in Science and Technology, 2017
The goal of this paper is to promote computational thinking among mathematics, engineering, science and technology students, through hands-on computer experiments. These activities have the potential to empower students to learn, create and invent with technology, and they engage computational thinking through simulations, visualizations and data…
Descriptors: Calculus, Probability, Data Analysis, Computation
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Hosack, Bryan; Lim, Billy; Vogt, W. Paul – Journal of Information Systems Education, 2012
An introduction to programming course can be a challenge for both students and instructors. This paper describes a study that introduced Web services (WS) and Service-Oriented Architecture in Information Systems 1 (IS 1) and Computer Science 1 (CS 1) programming courses over a two-year period. WS were used as an instruction tool based on their…
Descriptors: Computer Science Education, Programming, Introductory Courses, Internet
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Denner, Jill; Werner, Linda; O'Connor, Lisa; Glassman, Jill – Community College Review, 2014
Efforts to increase the number of women who pursue and complete advanced degrees in computer and information sciences (CIS) have been limited, in part, by a lack of research on pathways into and out of community college CIS classes. This longitudinal study tests three widely held beliefs about how to increase the number of CIS majors at 4-year…
Descriptors: Two Year College Students, Longitudinal Studies, Majors (Students), Career Choice
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Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne – Journal of the Learning Sciences, 2014
New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…
Descriptors: Programming, Computer Science Education, Learning Processes, Introductory Courses
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