Google for Education Innovation Academy

How do we Build a Culture of Inquiry and Data Use?

School systems have a shared responsibility to improve student learning outcomes. Likewise, for staff there is an obligation to provide extended opportunities to build on what they already know. High quality recording methods that ascertain growth mapped over time can identify trends and highlight threats allowing organisations to predict implications of applying a learning initiative or intervention. This can become complex and messy due to competing agendas and a variety of interpretations. For this reason, organisations have an obligation to develop a fair, ethical and shared understanding how data will be used and interpreted (Stoll & Fink,1996). A strong and user-friendly data system when properly implemented, empowers teachers to discover value in functions that bring student data to their fingertips (Brunner, Fasca, Heinze, Honey, Light, Mandinach & Wexler , 2005). Therefore, teachers require adequate learning support if they are to use data to improve practice

Managing the use of Artificial Intelligence (AI) in the classroom

As educators, we all understand the importance of ensuring that students submit their own work and are not cheated of their success by others. However, with the increasing use of artificial intelligence (AI) in the classroom, it can be difficult to ensure that students are not cheating on assignments. Fortunately, there are a number of measures that educators can take to minimise the possibility of cheating while still using AI to their advantage. Here are a few tips to help you manage the use of AI and minimise cheating by students on assignments. 1. Set Clear Guidelines The first step in preventing cheating is to set clear guidelines about the use of AI and make sure that students understand the expectations. Make sure students are aware that AI-generated work is not permitted and that any work submitted must be their own. 2. Monitor Student Activity Monitoring student activity through AI can help you identify any potential cheating. AI can be used to detect plagiarism and other sign

Impactful Instruction!

Deep Learning through balanced approaches to Direct Instruction and Inquiry-Based Learning. This blog post draws inspiration from Rachel Lehr's recent insights (2023) on the instructional framework employed by Dayton Public School, particularly their Instructional Playbook and an article from Jay McTighe and Harvey Silver (2020) called Instructional Shifts to Support Deep Learning. Lehr's message struck a chord due to its enlightening and encouraging nature. The strategies encapsulated within the playbook not only find their roots in a robust evidence base but also vividly illustrate the advantages of embracing a balanced approach to education. Dayton Public Schools' Instructional Playbook, as highlighted by Lehr, exemplifies a comprehensive and well-founded framework for effective teaching and learning. The strategies it contains are deeply rooted in educational research, showcasing the value of a well-rounded and diverse approach to education. This playbook serves as a t

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