Data-Driven Instruction In The Classroom Instruction
In the previous issue of this special issue, we have focused on various approaches to improving instructional processes. Mainly, we have focused on instruction and learning that is mediated through computer systems, that is, computer-based learning environments. It seems that most of the research in the fields of Educational Data Mining (EDM) and Learning Analytics (LA) has indeed been focused on analyzing what is happening within virtual learning environments. This is of no surprise, considering the history of these communities. Baker and Siemens (2014) describe the origins: “Much of the early work in EDM was conducted within intelligent tutoring systems […] and much of the work in LA began in Web-based e-Learning and social learning environments.” Although Baker and Siemens mention these beginnings in order to demonstrate the ever-widening range of data sources being discussed in the EDM/LA communities, all but one of their examples are computer-based learning environments (learning resources, science simulations, teacher newsgroups); their last example is school district grade data systems.
Still lacking in the mainstream data-driven approaches to studying educational settings is the very basic, most popular educational setting – that is, the classroom. Using data-driven methods to study the traditional classroom was suggested about the time EDM community first emerged (cf. Romero & Ventura, 2007), and some work has since been done in this direction (e.g., Blanchard, D’Mello, Olney, & Nystrand, 2015; Hershkovitz, Merceron & Shamaly, 2015; Martinez-Maldonado, Yacef & Kay, 2013 – just to name a few). Data concerning learning and teaching processes in traditional classrooms can be diverse and include, among others, teacher-student and student-student discourse and interactions, students’ emotional states, and–much more traditionally—student assignments and grades. These can be collected via observations, audio/video recording, or even log files (like in Martinez-Maldonado, Yacef, & Kay, 2013). Capturing data that describes learning in the classroom is the focus of the current issue. The articles in this issue present a large variety of data sources, data collection tools and data analysis techniques.