Skip to main content

Educational Research - Impact of Teacher Practice

It is the opinion of the author that educational research should extend beyond university academics; it is a highly valuable resource beneficial for educational facilities, educators, policy-makers and students themselves. It then becomes essential for teachers to be provided with the time and access to engage in the rigorous interplay with the research and if not, be endorsed the opportunity to connect with those who are to avoid misunderstandings that can be created by the popular media (Pezaro, 2015).

Well-informed research can make significant differences in the day-to-day practice of teachers as demonstrated by Barone and Mallette (2012). As editors of The Reading Teacher they were curious to discern the significant articles and books had influenced actual teaching practices in the classroom. Of their 219 individual respondents there were 119 influential pieces identified. Through researching these papers and books they ‘noticed that the authors’ voices were strong. The authors spoke directly to teachers sharing the strengths or complications of bring practice to their classroom. Research supported the practice, but research was in the background’ (p.5).

Pezaro (2015) proposes, in moving from research and theory to practice, educators are required to engage with the research in a context that is known, their classroom. To this end, educators seek opportunities where it can inform practice to enhance the educational outcomes for the student. This all comes about due to the willingness to collaborate, developing a research literate teaching culture.

Hattie (2012) assessed the effectiveness of programs, practices, and strategies that have been employed in schools internationally, synthesising fifteen years' data from over 900 meta-analyses. While most efforts to improve student outcomes had a positive impact, measured by Effect Size (ES), some interventions had greater impact on student development. Practices such as student self-reporting grades (ES 1.44), reciprocal teaching (ES .74), feedback (ES .73) and master learning (ES .58) had positive impacts being well above the nominated average of .40 ES, whereas ability grouping (ES.12), gender (ES .12), and student control over learning (ES .04) had lower impact (Hattie, 2012).

The consequences of Hattie’s investigation have a far-reaching impact on education as it identifies interventions that are commonplace. In spending too much time on less effective interventions educators lose opportunity to improve the possible outcome, whereas using this research, teachers can see new pathways that engage the student in rich and meaningful ways.

Another example of evidence-informed practice is Hunter's (2015) work with the High Possibility Classroom which grew out of Craft's (2011) research on creativity and learning in the digital age. In an attempt to identify the key factors needed to transform education into a creative partnership between curriculum and technological needs, it draws on wise creativity and possibility thinking. Hunter articulates the characteristics of exemplary classroom teachers’ and how they apply their knowledge to technology integration. It builds on the pedagogical framework of technological, pedagogical and content knowledge (TPACK) theory of technology integration (Mishra & Koehler, 2006). She identifies problem seeking and solving and the ability to create flexibility within the complexities of the classroom using technology is an inherently a creative act demonstrated by technology-savvy teachers (p.6). Hunter found that as educators let go, a space developed to explore and experiment increasing both teacher and student engagement. These teachers provided experiences where students explore and demonstrate their learning in real-life situations making the learning meaningful.


The benefits of educational research can go beyond just identifying what works and what doesn't, when applied it will drive and empower both quality teaching and learning. The notion that given the time, every student can and will learn is not a new concept; however, it is the principle that drives mastery learning. Returning to Hattie’s Visible Learning for Teachers (2012, p.269) he identifies mastery learning 0.58 and socio-economic status 0.57 have a similar effect sizes. Fox (2004) identifies mastery learning as a flexible way to differentiate based on student needs. In doing so it supports schools to translate research into differentiation into practice. For each student the learning goals remain the same; however, the content is reduced allowing students to focus on their areas of need and going deeper with this rather than content they have already mastered. Guskey (2009) describes the process of mastery learning as beginning with a pre-assessment of skills and knowledge to identify understanding that they have not learned. They then go through a series of small-individualized units created to remedy this gap. When the student is ready they complete an assessment based on the unit of work to show that they have mastered the knowledge and skill. This cycle repeats for each unit of work and includes individual feedback, personalized coaching and micro-teaching.

Note: This is part two of a four-part series on the importance of research to the practitioner.
References

Craft, A. (2011). Creativity and education futures: Learning in a digital age. Stoke on Trent: Trentham Books.

Fox, E.J. (2004). The Personalized System of Instruction: A Flexible and Effective Approach to Mastery Learning. In Moran, D.J. & Malott, R. W. (Eds) Evidence-Based Educational Methods, Elsevier Academic Press, Amsterdam.
Guskey, T. R. (2009). Mastery learning. In T. L. Good (Ed.), 21st century education: A reference handbook (Vol. I, pp. 194–202). Sage, Thousand Oaks, CA.
Hattie, J. (2012). Visible learning for teachers: Maximizing impact on learning, Routledge.
Hunter, J. (2015). Technology integration and the High Possibility Classroom, Routledge.
Mishra, P. & Koehler, M.J. (2006). Technological pedagogical content knowledge: A new framework for teacher knowledge. Teacher College Record, 108(6): 1017-1054.
Pezaro, C. (2015). Teacher as researches: what they do, where to find them and how academic researchers can engage with them. EduResearch Matters, Australian Association for Research in Education. Retrieved March 21, 2016 from
http://www.aare.edu.au/blog/?p=980

Comments

Popular posts from this blog

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

What does a post-industrial class look like? Part 2

This post is the second part of a series that I have been working on to identify what  does a post-industrial class look like? In my previous post , I looked at using video, collaborative discussion, grouping and student-centred learning. Why a large display and one to one? The large electronic display is used as it offers many benefits to a given lesson; these include demonstration and modelling as the teacher could showcase the application or video from the board (Moss, et al, 2007). It is easy to show the important features of particular web-based activities and have students interact with the material on their own devices. The board can accommodate different learning styles (Herrington & Harrington, 2006). Interactive boards can help tactile learners by touching and marking the board. Audio learners can have the class discussion and auditory multimedia, visual learners can see what is taking place as it develops at the board and it offers multimodal learning which can b