In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…

Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

The notion of algorithm may be perceived in different levels of abstraction. In the lower levels it is an operational set of instructions. In higher levels it may be viewed as an object with properties, solving a problem with characteristics. Novices mostly relate to the lower levels. Yet, higher levels are very relevant for them as well. We…

Pair programming is a strategy that grew out of industry and has shown promise for performance and retention in computer programming courses at universities and in industry. In this study, we examine whether pair programming is effective in K-12, what it is effective for, and how partners influence each other. We collected the data from 320 middle…

This study develops a Multiprog virtual laboratory for a mechatronics education designed to teach how to programme a programmable logic controller (PLC). The study was carried out with 34 students in the Department of Industry Education and Technology at National Changhua University of Education in Taiwan. In total, 17 students were assigned to…

Referent structures produced by the instructor, other experts, averaged experts, and the best students were compared with those of 71 college students for their ability to predict examination performance in computer-programming courses and to differentiate among levels of expertise. Differences among expert referents are discussed. (SLD)

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…

The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…