Abstract:

As lesson transcripts become increasingly accessible, there is a growing need for tools that can capture teaching quality from text alone, laying the foundation for scalable, AI-driven analysis. This study adapts the classroom-level components of the Dynamic Model of Educational Effectiveness (DMEE) into a low-inference codebook specifically optimized for textual data. The goal is to preserve the theoretical integrity of the original in-class observation instruments while ensuring that each indicator is operationalized through explicit verbal evidence, creating a robust framework suitable for both human annotation and future machine learning applications.

We started by analyzing all existing elements of low- and high-inference observation instruments, adding new sub-items to capture characteristics specific to classroom transcripts. Each element was reviewed to determine its dependence on nonverbal cues, precise timing, or holistic assessment. The elements were then classified according to a systematic discernability scheme—textually discernable, conditionally discernable, impossible to discern from the text, or omitted due to redundancy. Where possible, complex indicators were reformulated into smaller verbal events so that the main construct could still be presented in a concise manner.

This article describes in detail the methodological framework used to develop the final instrument. To establish content validity, we employed a structured expert panel review in which experts in the DMEE independently assessed the relevance and clarity of each indicator. The analysis showed high content validity, and only minor improvements were needed based on expert feedback. In the validated codebook, more than a hundred indicators are grouped into conceptual levels that distinguish simple turn-level codes from context-dependent or derived metrics.

The developed framework offers researchers and practitioners a DMEE theory-grounded, content-validated approach for analysing lesson transcripts at scale. It clearly shows which aspects of effective teaching can be captured from text alone and which remain poorly represented, thus defining a realistic scope for text-based classroom observation and laying the groundwork for subsequent reliability testing and semi-automated analysis.

Keywords:

Dynamic Model of Educational Effectiveness, classroom observation, transcript analysis, text-based analysis, codebook development, content validity, teacher evaluation.