The ACER Progressive Achievement approach includes PAT assessments that measure what students know, understand, and can do across the domains of Reading, Spelling, Vocabulary, Grammar and Punctuation, Maths, Science, Inquiry and Problem Solving in STEM Contexts, and Critical Reasoning. The results of PAT assessments are available immediately to…

Despite the promotion of data-driven or data-informed instructional practices in teacher education and professional development, past research indicates that teachers use a limited number of sources for student data to make short-term adjustments to their teaching in order to address deficiencies in student learning. Science teachers, with a more…

This essential science methods resource integrates principles of learning and motivation with practical teaching ideas for the elementary and middle school science classroom. It employs project-based learning (PBL) to enable educators to engage their students in meaningful, real-world questioning about the world. It provides concrete strategies…

Students classroom behaviours are complex and variable, involving multiple aspects such as students personality traits, learning attitudes, thinking styles and learning abilities, but traditional classroom behavioural assessment cannot comprehensively and reasonably assess students classroom learning status. The study adopts the improved Yolov5…

Data walls are a data use practice increasingly being adopted in western, Anglophone countries to display student academic achievement data. The purpose of data walls is to improve teaching and learning by helping teachers and/or students to identify patterns of growth and achievement, set goals, and plan instructional interventions or…

The generation, use, and analysis of educational data comes with many promises and opportunities, especially where digital materials allow usage of learning analytics (LA) as a tool in data-based decision-making (DBDM). However, there are questions about the interplay between teachers, students, context, and technology. Therefore, this paper…

Statewide technical assistance providers support many school teams through training, consultation, and coaching to improve systems and outcomes for mathematics for every student. They have the opportunity to work with many school psychologists, who often indicate they are more comfortable engaging in systems-level work for literacy, behavior, and…

The availability of large-scale learning data presents unprecedented opportunities for investigating student learning processes. However, it is challenging for instructors to fully make sense of this data and effectively support their teaching practices. This study introduces LearningViz, an interactive learning analytics dashboard to help…

Many data science applications involve generating questions, acquiring data and preparing it for analysis--be it exploratory, inferential, or modeling focused--and communicating findings. Most data science curricula address each of these steps as separate units in a course or as separate courses. Open-ended term projects, however, allow students…

Teacher-level factors are theoretically linked to student outcomes in data-based instruction (DBI; Lembke et al., 2018). Professional development and ongoing support can increase teachers' knowledge, skills, and beliefs related to DBI, as well as their instructional fidelity (McMaster et al., 2020). However, less is known about how each of these…

A school in South Carolina developed a strategic plan to implement a professional learning community structure in the school, where teachers work together to evaluate student data to improve instruction. However, teachers at the school did not understand how to use data-driven instructional practices to drive classroom instruction. The purpose of…

Various data systems have been long and pervasively used in schools to collect student data. However, very few educators are able to apply their collected data to improve their teaching. The purpose of this article is to investigate how middle school teachers adapt data mining protocols to enhance their teaching and to improve their students'…

Old habits die hard, particularly when they are part of the unexamined norms of schooling. In "Why Are We Still Doing That?," the best-selling authors of "Total Participation Techniques" lead a teacher-positive, empathetic inquiry into 16 common educational practices that can undermine student learning: (1) Round robin reading;…

In view of the traditional teaching mode, this study focuses on the application of big data in personalized English teaching in colleges and universities. It aims at improving the teaching effect by using big data. By combining personalized teaching and big data theory, this paper analyzes the current situation of college English teaching,…

The current study explored preservice and inservice teachers' perspectives on data literacy for teaching. Semi-structured interviews were employed with 12 teacher candidates in elementary and special education. The findings revealed participants' misconceptions regarding formative and summative data; their understanding of the value of formative…