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Using Learning Analytics in the Amazonas: Understanding Students' Behaviour in Introductory Programming

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Pereira, Filipe D.; Oliveira, Elaine H. T.; Oliveira, David B. F.; Cristea, Alexandra I.; Carvalho, Leandro S. G.; Fonseca, Samuel C.; Toda, Armando; Isotani, Seiji – British Journal of Educational Technology, 2020

Tools for automatic grading programming assignments, also known as Online Judges, have been widely used to support computer science (CS) courses. Nevertheless, few studies have used these tools to acquire and analyse interaction data to better understand the students' performance and behaviours, often due to data availability or inadequate…

Descriptors: Introductory Courses, Programming, Outcomes of Education, Student Behavior

Using Keystroke Analytics to Improve Pass-Fail Classifiers

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Casey, Kevin – Journal of Learning Analytics, 2017

Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…

Descriptors: Keyboarding (Data Entry), Educational Research, Data Collection, Data Analysis

Proceedings of the International Conference on Educational Data Mining (EDM) (9th, Raleigh, North Carolina, June 29-July 2, 2016)

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Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016

The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…

Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction