Conference Agenda

Issues in mathematics education are wide-ranging, with the subject often perceived as hard, formulaic, and consisting of a series of unrelated abstract concepts, with a strong focus on assessment (Bray & Tangney, 2017). Historically an over-reliance on skills and procedures has led to a lack of mathematical fluency and conceptual understanding, with problem solving viewed as little more than worded calculations (Schoenfeld, 2016). The main drivers of reforms in mathematics curriculum internationally focus on efforts to address these issues by, at least in part, giving greater considerations to the student at the centre of the learning. Maths students should be supported to develop a positive disposition towards the subject, by highlighting connections between the different mathematical strands (NCCA, 2017) and teaching for robust understanding (Schoenfeld, 2017) to ensure maths becomes more relevant for school and society in general.

Recent iterations of maths education reforms continue to show that changing how we teach mathematics is difficult, teachers struggle to find time to engage with reform or create new resources and as a result tend to rely heavily on textbooks (O’Meara & Milinkovic, 2023). Although various technological advances have been heralded as a “silver bullet” that will solve the issues with student engagement with mathematics, take-up and implementation of such resources by teachers has often remained at the periphery (Bennison & Goos, 2010). Many reasons have been cited as barriers to teacher uptake of new technological developments, including systemic issues such as class-size, timetabling and cost (Bray & Tangney, 2017), as well as access and logistical problems. However, another pressing issue, is a need for professional development (PD) for teachers (OECD, 2015).

There is consistent evidence indicating that a sustained and experiential approach to PD is essential to support teacher change (Desimone, 2011). It is essential that practitioners are provided with opportunities to develop their own understanding of the value and relevance of any proposed change, as well as to recognise the impact that it might have on their practice and on student outcomes (Kärkkäinen, 2012).

The latest technological advancement that is predicted to have a significant impact on our societies and futures is generative AI (GenAI). Many questions have arisen about its potential impact on education, which are speculated to be both positive and negative (Giannini, 2023). While there are ethical concerns about the black box nature around the understanding of the AI processes, and the veracity of the information which it provides (Kaplan-Rakowski et al., 2023), there are also significant fears around cheating and plagiarism. However, when used appropriately, GenAI offers many opportunities, with UNESCO suggesting it can be used for activities ranging from idea generation to a reflection aid (Sabzalieva & Valentini, 2023). Of relevance to this work is the potential for GenAI to support teachers in the generation of, and reflection upon, lesson plans and resources that address the issues in mathematics education highlighted above. Hence the “two birds” reference in title – teachers are learning how to engage with GenAI while creating lessons which aim to meet the goals of curriculum reform. However, in order to support this, appropriate PD must be provided.

Constructivism and constructionism are the theoretical frameworks that underpins this research, acknowledging an approach in which both the technology and the user are constructing knowledge (Ackermann E., 2001). As part of a wider PD engagement with schools experiential GenAI workshops are being designed and delivered. The workshops support teachers through an immersive, iterative experience, to create and reflect upon lesson ideas, lesson plans and rich learning experiences, that give context and purpose to their lessons.

The generation and use of digital data and analyses in education comes with promises and opportunities, especially where digital materials allow use of Learning Analytics (LA) as a tool in Data-Based Decision-Making (DBDM). LA implies, analysing educational data to understand and optimise learning and learning environments (Siemens & Baker, 2012). In this paper we discuss LA as “a sophisticated form of data driven decision making” (Mandinach & Abrams, 2022, p. 196) as we explore how LA is used to support mathematics teaching and learning with digital materials in classroom practice. Data driven decision making or DBDM has been defined by Schildkamp and Kuiper (2010) as “systematically analyzing existing data sources within the school, applying outcomes of analyses to innovate teaching, curricula, and school performance, and, implementing (e.g., genuine improvement actions) and evaluating these innovations” (p. 482). DBDM is a key for the interpretation of LA, and can use any form of data, but in this review, the term DBDM is restricted to digital data. Using LA as a tool for DBDM could streamline data, making it more readily interpretable. However, questions remain about how usage can translate into practice (Mandinach & Abrams, 2022).

Quality of technology integration is not merely about technology use, but also about pedagogical use (Ottestad & Guðmundsdottir, 2018), about transformation and amplification of teaching as well as learning through use of technology (Consoli, Desiron & Cattaneo, 2023). LA within Digital Learning Material (DLM) can offer learners adaptive functions seamlessly embedded in DLMs or, provide learners (and teachers) compiled student assessments in relation to learning goals extracted from learning activities (Wise, Zhao & Hausknecht, 2014). The role of the teacher in student learning is clearly of central importance (Hattie & Yates, 2013; Yackel & Cobb, 1996), and teachers have a key responsibility to make digital technology a recourse in teaching to support student learning (Scherer, Siddiq & Tondeur, 2019).

This paper present findings from an exploratory systematic scoping review which was conducted regarding the use and impact of LA and DBDM in classroom practice to outline aspects related to Digital Learning Material (DLM), teacher usage, and student learning in the context of K-12 mathematics education.

A scoping review was deemed most appropriate since it can be performed even if there is limited number of published primary research (Gough, Oliver & Thomas, 2017), fitting new research areas such as LA, as it provides “a technique to ‘map’ relevant literature in the field of interest” (Arksey & O’Malley, 2005, p. 20), as well as combine different kinds of evidence (Gough, et al., 2017).