Question 1

How did you build a Taxonomy of 317 In-classroom Teacher Behaviours?

Accepted Answer

We followed a rigorous three-stage research process to construct our Taxonomy of In-classroom Teacher Behaviours.

Stage 1 | Identify behaviours 
We reviewed the global evidence base, analysing over 19 pedagogic approaches, 102 instructional strategies, 46 formative assessment strategies, and 42 thinking routines. From this research, we compiled an initial set of 72 specific, observable, and measurable in-classroom teacher behaviours.

Stage 2 | Organise behaviours 
We examined the specific purpose of each behaviour and grouped them into three functional categories: Instructional, Managerial, and Relational.

Stage 3 | Validate and expand behaviours 
To ensure our framework reflected reality, we analysed thousands of hours of video-recorded classroom lessons across India. This allowed us to confirm which behaviours appear consistently in real teaching contexts. Through this validation, we expanded our taxonomy from the initial 72 to 317 in-classroom teacher behaviours.

To clarify the three categories:

• Instructional behaviours directly support and facilitate learning.
 • Managerial behaviours ensure smooth use of time, space, and transitions.
 • Relational behaviours build trust and psychological safety, so students feel confident to participate and take academic risks.

Together, these 317 in-classroom teacher behaviours give school leaders and teachers a clear, consistent, and practical way to see, measure, and strengthen teaching where it matters most: inside the classroom.

Question 2

Why should our school switch from an existing observation framework to your Taxonomy of In-classroom Teacher Behaviours?

Accepted Answer

To answer this, we conducted a rigorous side-by-side comparison of our Taxonomy of In-classroom Teacher Behaviours against the Danielson Framework, the World Bank's Teach Primary, and the traditional classroom observation rubrics widely used in Indian schools. We evaluated them for objectivity, precision, and transferability. The results were clear: while these traditional frameworks rely on high-inference opinions about quality, our Taxonomy relies on low-inference facts about execution.

For example, the Danielson Framework for Teaching provides an aspirational vision of a "Distinguished" classroom but often lacks the diagnostic map to get there. It requires observers to evaluate "unseen" domains like Planning and Preparation or Principled Teaching, which cannot be directly observed during a lesson. Furthermore, it relies on high-inference judgments of internal states like "Engagement," where an observer must guess if a student is genuinely cognitively engaged or merely compliant. In contrast, our Taxonomy strips away this guesswork by using the Time, Sequence, and Cluster Lenses to analyze visible mechanics. We do not ask if a teacher's plan was coherent; we measure if the teacher spent 20 minutes lecturing to the whole class versus 2 minutes listening to students, diagnosing the root cause of low engagement rather than just rating it.

Similarly, the World Bank’s Teach Primary tool relies on a "Snapshot" methodology, where observers scan the room for just 1-10 seconds at specific intervals (minutes 4, 9, and 14). This approach misses the continuous flow of instruction and is vulnerable to the "Illusion of Competence," where a class shouting answers in unison might receive a "High" quality rating for checking understanding. Our Taxonomy replaces these intermittent snapshots with continuous second-by-second coding. We capture the full reality by revealing, for instance, if a "High Quality" choral response is actually a "Choral Calculation Loop" that masks the fact that most students are not learning. Unlike Teach Primary’s subjective "Low, Medium, High" ratings, our binary coding ensures that feedback is based on indisputable facts about who received instruction and for how long.

Finally, the traditional classroom observation rubrics widely used in Indian schools focus heavily on Content (what is taught), Resources (what teachers use), and Tasks (what students do). Because the content, resource and tasks change every day, this feedback is hard to transfer from one lesson to the next. Our Taxonomy focuses on the Fourth Layer: In-classroom Teacher Behaviour. By measuring the 317 foundational habits that a teacher brings to every class regardless of the subject, such as giving instructions or using non-verbal behaviour management cues, we provide data that is objective, transferable, and actionable. You should switch because you cannot improve what you cannot accurately measure.

Question 3

How do you ensure the Taxonomy does not penalise legitimate, varied teaching styles?

Accepted Answer

During a Classroom Audit, we never judge a teaching approach or style as "good" or "bad". We simply code exactly what teachers do and how those choices influence student learning. We do not evaluate the content, the teaching resources, or the instructional strategy the teacher chooses. Instead, we focus exclusively on observable, timestampable in-classroom teacher behaviours.

Our framework applies universally. The Taxonomy includes 317 instructional, managerial, and relational behaviours that teachers use across different subjects, grade levels, and pedagogic approaches. To build this framework, we studied and deconstructed 19 pedagogic approaches, 102 instructional strategies, 46 formative assessment strategies, and 42 thinking routines. We converted these diverse strategies into specific, measurable actions.

This breadth ensures fair representation for every teacher. Whether a teacher prefers to lecture, model, facilitate discussion, guide inquiry, or organise collaborative learning, our tool captures the value they deliver. We measure the learning opportunities a teacher creates for students to think, respond, practise, and stay engaged.

We do not measure aesthetics, personality, or performance style. Our goal helps every teacher reflect on their specific in-classroom teacher behaviour choices. This allows them to make intentional changes that strengthen student learning while continuing to teach in a way that fits their personality, subject, and classroom context.

Question 4

How does your Classroom Audit align with NEP 2020 and NCF 2023?

Accepted Answer

Our Classroom Audit helps your school meet the rigorous expectations of the National Education Policy 2020 (NEP 2020) and the National Curriculum Framework 2023 (NCF 2023) inside every classroom.

NEP 2020 and NCF 2023 demand specific shifts in pedagogy, explicitly calling for student-centred and competency-based learning alongside experiential learning. They prioritise concept-based instruction, project-based learning, and art-integrated learning.

These policies require students to think, respond, create, and apply, rather than just listen and copy. Our Taxonomy of In-classroom Teacher Behaviours tracks the exact actions your teachers take in real time to facilitate this. It reveals precisely whether students are actively learning or remaining passive.

The Whole-school In-classroom Teacher Ethogram identifies exactly where your current teaching meets NEP and NCF standards and where specific habits block deeper learning. The In-classroom Teacher Behaviour Scorecards give each teacher a clear path to improve the specific behaviours that increase student participation, questioning, creativity, and understanding.

With our Classroom Audit and targeted follow-up coaching, your school moves from policy promises in brochures to policy execution in every lesson. This ensures every student learns the way these national policies intend.

Diagnose before you intervene.

What is a Whole-school In-classroom Teacher Ethogram?

What is an In-classroom Teacher Behaviour Scorecard?

What is the Taxonomy of In-classroom Teacher Behaviours?

What is a Classroom Audit?

Noldenbirge

Navigation