NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 7 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Zhang, Yingbin; Pinto, Juan D.; Fan, Aysa Xuemo; Paquette, Luc – Journal of Educational Data Mining, 2023
The second CSEDM data challenge aimed at finding innovative methods to use students' programming traces to model their learning. The main challenge of this task is how to decide which past problems are relevant for predicting performance on a future problem. This paper proposes a set of weighting schemes to address this challenge. Specifically,…
Descriptors: Problem Solving, Introductory Courses, Computer Science Education, Programming
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Shacham, Mordechai; Cutlip, Michael B.; Brauner, Neima – Chemical Engineering Education, 2009
A continuing challenge to the undergraduate chemical engineering curriculum is the time-effective incorporation and use of computer-based tools throughout the educational program. Computing skills in academia and industry require some proficiency in programming and effective use of software packages for solving 1) single-model, single-algorithm…
Descriptors: Computer Software, Computer Literacy, Problem Solving, Chemical Engineering
Cetintas, Suleyman; Si, Luo; Xin, Yan Ping; Hord, Casey – International Working Group on Educational Data Mining, 2009
This paper proposes a learning based method that can automatically determine how likely a student is to give a correct answer to a problem in an intelligent tutoring system. Only log files that record students' actions with the system are used to train the model, therefore the modeling process doesn't require expert knowledge for identifying…
Descriptors: Programming, Evidence, Intelligent Tutoring Systems, Regression (Statistics)