Measuring effective teaching: Student perceptions of their modern languages lessons in England
Introduction
High-quality teaching is the most important school-based factor associated with student achievement scores (Schleicher, 2016). However, the identification and development of good classroom practice is known to be complex and difficult (Kane, Kerr, & Pianta, 2014). No wonder then, that significant time and resources have been invested in the identification of hallmarks of quality in teaching to inform quality assurance and programmes of initial and in-service teacher education in education systems around the world (OECD, 2017).
In much of the Western world, particularly in English-speaking jurisdictions such as Australia, England and the United States of America, high-stakes accountability systems evaluate teaching quality predominantly via students’ test scores, sometimes alongside structured observations of teachers’ classroom practice (Bowe & Gore, 2017). However, the large-scale Measures of Effective Teaching (MET) project questioned the validity and reliability of these measures and urged a more balanced approach to teacher evaluation involving a combination of multiple data sources (Bill & Melinda Gates Foundation, 2012). One currently underutilised source of information about teachers’ work is students’ own ratings of the effectiveness of their lessons. Student perception surveys (SPS) are “a cheap and easy source of good feedback about teaching behaviours from a range of observers who can draw on experience of many lessons” (Coe, Aloisi, Higgins, & Major, 2014, p. 4). Beyond their use for accountability purposes, there has also been much research interest in the potential for well-designed feedback and evaluation systems, including SPS, to support teacher’s professional learning (Bill & Melinda Gates Foundation, 2013; Schleicher, 2011).
The study described in this paper involves the design and testing of a student perception survey tool (SPS_ML) to provide data about the effectiveness of teaching and learning in modern languages (ML) classrooms in England. An analysis of the students’ responses highlights both strengths and areas for development in the subject-specific pedagogies employed by ML teachers across fourteen secondary schools. I make the case that the utility and validity of tools for teacher evaluation can be enhanced by adapting such tools to gather data of relevance to subject specialist teachers wishing to use targeted feedback to improve their practice.
Section snippets
Frameworks to identify high-quality teaching
High-quality teaching is commonly defined as teaching practices that are associated with improved student outcomes, encompassing both student attainment and also harder-to-measure outcomes such as student enjoyment and wellbeing (Kennedy, 2016). Many attempts have been made to define the attitudes, knowledge and skills that teachers require in order to be effective professionals. It is, difficult to identify what makes ‘great teaching’ but in recent years researchers have arrived at a degree of
Research questions
In order to explore the performance and perceived usefulness of a newly designed, subject-specific student perception survey (the SPS_ML), I constructed the following research questions:
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Does the SPS_ML offer reliable and valid measures of effective ML teaching?
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What does the SPS_ML reveal about students’ experiences of ML lessons?
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To what extent is the data gathered by the SPS_ML considered useful for teacher learning?
Instrument development
The student survey adapted for use in this study is the Colorado Student Perception Survey (CSPS), which was developed and rigorously tested as a part of the MET project (Bill & Melinda Gates Foundation, n.d.). Responses from one set of classrooms were used to predict value-added gains in other classrooms taught by the same teacher, thus controlling for the possible effects of individual student prejudices and other confounding factors (Colorado Education Initiative, 2013). The CSPS is a
Results and discussion
Firstly, I explore the performance of the SPS_ML and the extent to which there is alignment between teacher and student perceptions. The overall results of the survey are reported and the implications of these for ML teachers’ development are discussed. Finally, HoDs’ responses to the SPS_ML and their views as to the potential of the tool to inform teacher learning are discussed.
Conclusions
This study set out to answer the following two research questions:
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Does the SPS_ML offer reliable and valid measures of effective ML teaching?
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What does the SPS_ML reveal about students’ experiences of ML lessons?
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To what extent is the data gathered by the SPS_ML considered useful for teacher learning?
The SPS_ML tool was found to have high levels of internal reliability and provided data that correlated with a range of other known measures of effective teaching. Three distinct, languages-specific
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