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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
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
Cigdem, Harun – Contemporary Educational Technology, 2015
This study focuses on learners' self-regulation which is one of the essential skills for student achievement in blended courses. Research on learners' self-regulation skills in blended learning environments has gained popularity in recent years however only a few studies investigating the correlation between self-regulation skills and student…
Descriptors: Metacognition, Computer Science Education, Measures (Individuals), Blended Learning
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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