This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students' work is based on a…

Current research surrounding online computer science education emphasizes the need for high-quality professional development opportunities. However, there is a gap in research in the inclusion of online computer science educators to identify needs and strategies that make the online computer science courses effective. Through a…

The primary purpose of this study is to investigate CT skills development process in learning environments. It is also aimed to determine the conceptual understanding and measurement approaches in the studies. To achieve these aims, a systematic research review methodology was implemented as the research design. Empirical studies on computational…

Block-based visual programming tools, such as Scratch, Alice, and MIT App Inventor, provide an intuitive and easy-to-use editing interface through which to promote programming learning for novice students of various ages. However, very little attention has been paid to investigating these tools' overall effects on students' academic achievement…

Background and Context: Computational thinking (CT) is considered as a valuable literacy for all students, and its inclusion in compulsory schooling could increase the numbers of underrepresented students who pursue computing-related careers. Computer Science Unplugged (CSU) had success in making computer science (CS) accessible to K-12 students…

Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDM offers promising solutions to complex educational problems. Given the rapid increase in the availability of big data in education and software…

Background and Context: EarSketch was developed as a program to foster persistence in computer science with diverse student populations. Objective: To test the effectiveness of EarSketch in promoting intentions to persist, particularly among female students and under-represented minority students. Method: Meta-analyses, structural equation…

In the 1960s, the MIT (Massachusetts Institute of Technology) developed a programming language called LOGO. Underpinning this invention was a profound new philosophy of how learners learn. This paper reviews research in the area and asks how one notion in particular, that of a microworld, may be used by secondary school educators to build powerful…

Educational data mining can miss or misidentify key findings about student learning without a transparent process of analyzing the data. This paper describes the first steps in the process of using low-level logging data to understand how middle school students used Alice, an initial programming environment. We describe the steps that were…

For many years computing in New Zealand schools was focused on teaching students how to use computers, and there was little opportunity for students to learn about programming and computer science as formal subjects. In this article we review a series of initiatives that occurred from 2007 to 2009 that led to programming and computer science being…

In June 2018 the Canadian Mathematics Education Study Group/Groupe Canadien d'étude en didactique des mathématiques (CMESG/GCEDM) held its 42nd meeting in the idyllic setting of Squamish, British Columbia. This meeting marked the first time CMESG/GCEDM had been in British Columbia since 2010 and the first time it had been held at Quest University.…

The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

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…