In most universities around the world, student writing and text-based teaching materials are routinely uploaded to institutional Learning Management Systems (LMS) and form part of the familiar machinery and practice of higher education. While teachers in higher education can and do reflect on their practice through engaging with student language, both written and spoken, there is neither the time nor the space to do this at scale in larger classes. Where student language is systematically examined it is typically in the service of assessment, including checking for plagiarism, but it is seldom consulted in systematic ways for improving teaching, let alone compared to curricula materials and teacher language. Exploring the relation between learner and teacher texts presents an opportunity to illuminate both student learning and our teaching. In developing Quantext we aim to make it easy for teachers to develop their own theories of practice and to gain incremental pragmatic insights. From our early pilot studies we have found that teachers see the relevance and potential of text analysis and Quantext. Potential applications include: insight into how students are interpreting questions, how question wording can encourage thoughtful responses or simple reporting of facts, identifying the source of misconceptions in teaching materials.
Even though analysis and synthesis of text are central to teaching and learning in higher education, and even though this work is conceptually difficult, little attention is paid to how students understand and interpret teacher language in constructing their own academic writing (Laurillard,1993). While there is certainly educational research around how students come to understand academic discourse (e.g. Marton & Säljö, 1976), around teaching academic writing (Lea & Street, 1998), and around the link between language and learning (e.g. Gee, 2015; Wells, 1994; Halliday, 1993), translating this research into actionable insights for teachers, particularly of larger classes, remains elusive.
“We should expect to find our language re-expressed in the language of our students and herein lies an opportunity to evaluate our impact as teachers.”
From a philosophical perspective there is nothing very new here but it bears repeating. What we write or speak about, is intimately related to what we have read or listened to (Bakhtin,1981). Essential meaning constitutes and is constituted by our culture and is inseparable from our language (Bruner, 1990); and this includes disciplinary culture and language. From Hattie’s work, applied to higher education (2015) we know that student factors account for around 50% of the variance in learning achievement. However, the next largest chunk that teachers have control over is teaching (20-25%). What we do as teachers makes a difference and it should, or why are we teaching at all? We should expect to find our language re-expressed in the language of our students and herein lies an opportunity to evaluate our impact as teachers.
According to Hattie (2015), teachers evaluating their impact is one of the key factors affecting student achievement. Intuitively, evaluating the clarity, the salience, the perspicacity of our educational dialogues should help us to guide their course. In turn, productive educational dialogue should support students to not only create meaning congruent with curricula expectations but also to develop the broader attributes we associate with university graduates.
Our goal in developing Quantext is to bring to practicing teachers simple analytic tools that help us to evaluate our impact as teachers. Whether we achieve that goal remains to be seen but we welcome all teachers and students on our journey to try.
To dive in and start using Quantext, visit our demonstration site. Quantext was designed for classroom teachers but we’re finding educational researchers and teachers who are researching their own practice, think it is pretty cool too! Quantext can be adapted to work with online discussion posts, teaching and course evaluations. Contact us to discuss your specific application.
If you’d like to look at, or contribute to, the Quantext code, visit us on github, http://github.com/quantext/quantext
Not sure what to do? Follow us on Twitter!Follow @quantext
Bakhtin, M. M. (1981). The dialogic imagination. Austin:Gee, J. (2015). Social linguistics and literacies: Ideology in discourses: Routledge.
Bruner, J. (1990) Acts of Meaning. Harvard University Press.
Gee, J. (2015). Social linguistics and literacies: Ideology in discourses: Routledge.
Halliday, M. A. K. (1993). Towards a language-based theory of learning. Linguistics and Education, 5(2), pp. 93–116.
Hattie, J. (2015) The Applicability of Visible Learning to Higher Education. Scholarship of Teaching and Learning in Psychology. 1(1), pp. 79 –91.
Laurillard, D. (2002) Rethinking University Teaching: a framework for the effective use of educational technology. RoutledgeFalmer, London.
Lea, M. & Street, B (1998) Student writing in higher education: An academic literacies approach. Studies in Higher Education. 23(2), pp. 157-172.
Marton, F. and Saljo, R. (1976). On qualitative differences in learning: I Outcome and process. British Journal of Educational Psychology, 46(1), pp. 4–11.
Wells, G. (1994). The complementary contributions of Halliday and Vygotsky to a “language-based theory of learning”. Linguistics and Education, 6(1), pp.41-90.