Fine-Grained, Nomination Coding in the Support Domain: Promising Teacher Discourse Measures

Abstract

In this study, we report results from a novel coding of the Measures of Effective Teaching (MET) Study data that offers evidence on a set of teacher discourse measures in the domain of teacher support including: public praise vs. admonishment, autonomy support vs. controlling language, strategy suggestion vs. lack thereof, and discourse supporting (vs. undermining) learning mindsets. Novel coding of these constructs is paired with extant measures of instruction and achievement in the MET data. Several of the newly coded discourse measures have promising features, including high lesson- and teacher-level variability, and convergent and discriminant validity with existing protocols. We also report possible associations with change in achievement over two years.

Keywords:

• Classroom observation
• discourse
• support
• engagement
• motivation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The use of fine-grained instructional measures was more common in the process-product era of research, see summaries in Brophy (1986) and elsewhere.

Additional information

Funding

This work was supported by a grant from the Student Experience Research Network (formerly Mindset Scholars Network), K-12 Teachers and Classrooms Research Portfolio.