The following is taken from the Description of Work:
Low achievement in science and mathematics is a common concern for all European countries. (Rocard et al, 2007; ECEA/Eurydice, 2011a) It is an issue associated not only with the effectiveness of teaching and learning, but also with providing an equitable system of education. A range of approaches have been developed to support underperforming students and to attempt to close the persistent gap between the highest and lowest achieving students. In this project, low achievement refers to student performance that is below the expected level of attainment. Under-performance occurs for a wide variety of reasons. However, this project focuses on school-related factors and does not address those linked to specific learning disabilities such as dyscalculia and does not address the provision of support exclusively related to special needs education. Moreover, research (Malony et al, 2013) shows that stereotyped attitudes have an impact on achievement in mathematics and this may also be the case for science. Thus attention will need to be paid to strategies to challenge such attitudes on the part of teachers and students.
The project draws on evidence from large scale systematic reviews of educational interventions which reveal that the effect size (see section 3 for an explanation of this measure) on achievement of interventions that focus on the development of teaching using formative interpretations of assessment in classrooms is significantly greater than most other intervention approaches(Hattie, 2009). A key element of this diagnostic approach to teaching using assessment and intervention relates to the quality of the information generated by the various feedback loops that exist in the classroom setting and the involvement of the students within this process. Hence, the introduction of innovative technological tools2to create a digital environment which enhances connectivity and feedback to assist teachers in making more timely formative interpretations has the potential to amplify the quality of the evidence about student achievement in real-time for access by both students and teachers.
This is a complex educational challenge, since there is no clear characteristic of low achievers in mathematics and science. While they share the common feature of underachievement, such groups typically contain a disproportionate number of those from disadvantaged social, cultural and racial groups, and in some countries without a good command of the first language of the classroom (Boaler, Wiliam, & Brown, 2000; Ireson & Hallam, 2001). Established approaches for working with such students are frequently characterised by a ‘deficit’ model of their potential which entails repeating material from earlier years, broken down into less and less challenging tasks, focused on areas of knowledge which they have previously failed and which involve step-by-step, simplified, procedural activities in trivial contexts. In contrast, the TIMSS seven-nation comparative study shows that high achieving countries (Hiebert et al., 2003) adopt approaches which preserve the complexity of concepts and methods, rather than simplifying them. In addition, evidence indicates that attitudinal factors on the part of both students and teachers can have a powerful impact on achievement, particularly with this group of students. In mathematics, anxiety and stereotyping, for example, are known to have a significant impact on the performance of students and these factors can also have an impact on how teachers approach this subject, particularly in primary school where they may not be ‘subject experts’ (Malony et al., 2013). It is not known whether similar factors impact on science, although students in scientific topics which use a significant amount of mathematics might be expected to exhibit similar problems. It is also possible that the use of technology to support interventions may introduce an additional barrier through teacher and students attitudes to its use in science and mathematics education. This project will build on the evidence of research from, for example, the LAMP (Ahmed, 1987), RAMP (Ahmed & Williams, 1991) and IAMP (Watson, De Geest, & Prestage, 2003) projects in mathematics teaching and the CASE (Michael Shayer & Adey, 2002) project in science teaching in the UK and elsewhere which adopted approaches focused on the proficiencies of the students rather than their deficiencies.