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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
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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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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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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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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