Transforming Education with NLP: Smarter Schools Through Language Technology

In education, feedback isn’t just a routine task—it’s the foundation of progress, innovation, and meaningful change. Every comment from a student, parent, or teacher holds a story, a perspective, and an opportunity for improvement. But transforming these stories into actionable insights can be overwhelming without the right tools. That’s where Natural Language Processing (NLP) and Microsoft Azure’s advanced suite of tools come in. Together, they don’t just analyse feedback—they unlock its full potential, empowering schools and Multi-Academy Trusts to make smarter, data-driven decisions. 

Why Feedback Analysis is the Game-Changer Modern Education Can’t Ignore

Education leaders today face a complex balancing act: improving student outcomes, supporting teacher well-being, and fostering parent engagement—all while navigating limited resources and increasing expectations. Feedback analysis is the key to addressing these challenges effectively. By leveraging NLP and Azure’s cutting-edge technology, schools can:

• Understand Student Sentiment: Gain insights into how students feel about curriculum changes, teaching methods, or school culture.

• Empower Teachers: Analyse teacher feedback to identify pain points, improve resource allocation, and boost job satisfaction.

• Engage Parents: Uncover parent concerns about communication, policies, or school safety, and address them proactively.

• Streamline Admissions: Optimise the admissions process by identifying what attracts—or deters—prospective families.

With NLP, feedback isn’t just data—it’s a roadmap for transformation.

Imagine a school introducing hybrid learning for the first time. Initial feedback might reveal students feeling unsupported due to insufficient online resources. At the same time, parents might raise concerns about the lack of communication regarding tech platforms. Addressing these issues early can improve the program’s success and build trust within the community.

Ready to Transform Feedback into Action?

Imagine having the tools to not just collect feedback, but to truly understand it—and act on it. With Deesha, powered by Natural Language Processing (NLP) and Microsoft Azure, you can turn every comment, concern, and suggestion into actionable insights that drive real change in your school or trust.

• Save Time: Stop sifting through endless feedback manually. Let Deesha do the heavy lifting.

• Make Smarter Decisions: From improving student outcomes to supporting teacher well-being, Deesha helps you prioritise what matters most.

• Build Trust: Proactively address parent concerns and streamline admissions to create a positive experience for your community.

Don’t let valuable insights slip through the cracks. Reclaim your time and empower your school with data-driven decisions.

Turning Feedback into Action: Key Areas for Transformation 

1. Transforming Admissions with Data-Driven Insights

Admissions are your first opportunity to make a lasting impression on parents. A smooth, straightforward process builds trust and confidence, while delays or unclear steps can quickly turn families away. But how do you identify and fix these issues before they impact your school’s reputation? The answer lies in feedback analysis—and with Deesha, powered by Microsoft Azure, you can turn admissions feedback into actionable improvements.

The Challenge: Declining Admissions Yield

Imagine this: your school has a strong applicant pool, but your admissions yield rate is dropping. Surveys reveal a recurring theme—parents are frustrated.

Example Feedback:

• “The online application portal is hard to navigate.”

• “Deadlines were unclear, which caused a lot of stress.”

Without a clear way to analyse this feedback, it’s easy to miss the root causes of these frustrations.

The Solution: Deesha and Azure Text Analytics

Using Azure Text Analytics, the school analyses feedback to identify specific issues. This is followed by creating actionable changes like improving form design or sending clearer communication. 

Code Example: 

from azure.ai.textanalytics import TextAnalyticsClient 

from azure.core.credentials import AzureKeyCredential  

endpoint = "<your_endpoint>" 

key = "<your_key>" 

client = TextAnalyticsClient(endpoint=endpoint, credential=AzureKeyCredential(key)) 

admissions_feedback = [ 

    "The online application portal is hard to navigate.", 

    "Deadlines were unclear, which caused a lot of stress.", 

    "The staff was incredibly helpful and prompt!" 

] 

response = client.analyze_sentiment(documents=admissions_feedback) 

for idx, document in enumerate(response): 

    print(f"Feedback: {admissions_feedback[idx]}\nSentiment: {document.sentiment}, Scores: {document.confidence_scores}") 

Example Outcome:
By analysing feedback, one school discovered that unclear deadlines were a major source of stress for parents. They responded by sending clearer reminders and simplifying their application timeline—resulting in a 20% increase in completed applications.

Why This Matters for Your School

• Boost Parent Confidence: A seamless admissions process builds trust and sets the tone for a positive relationship with families.

• Increase Enrolment: Addressing pain points can lead to higher yield rates and more completed applications.

• Save Time: Deesha automates the analysis process, freeing up your team to focus on strategic improvements.

Ready to Revolutionise Your Admissions Process?

Deesha makes it easy to turn feedback into action, helping you create a smoother, more efficient admissions experience for parents and staff alike.

👉 Contact us today to see how Deesha can transform your school’s admissions process.

2. Enhancing Teacher and Student Experiences

Teachers and students are the lifeblood of every school. Their satisfaction and engagement directly shape learning outcomes, school culture, and overall success. But understanding their needs and concerns isn’t always straightforward. That’s where feedback analysis comes in—and with Deesha, powered by Microsoft Azure, you can turn insights into action to create a better experience for everyone.

The Challenge: Overwhelmed Teachers and Disengaged Students

Picture this: teachers are voicing concerns about unmanageable workloads, while students are frustrated with outdated classroom resources. Without clear data, it’s hard to know where to start or how to prioritise solutions.

Example Feedback:

• Teachers: “The workload is overwhelming, and I don’t have enough time to plan lessons effectively.”

• Students: “Our textbooks are outdated, and the classroom technology doesn’t work properly.”

These issues can lead to burnout, disengagement, and even higher turnover rates among staff.

The Solution: Deesha and Azure Synapse Analytics

With Deesha, you can go beyond surface-level feedback to uncover the root causes of these challenges. By integrating feedback data with performance metrics using Azure Synapse Analytics, you gain a comprehensive view of what’s really happening in your school.

How It Works:

1. Collect Feedback: Gather input from teachers and students through surveys, interviews, or even voice and video recordings.

2. Analyse Trends: Use Deesha to identify patterns, such as workload concerns correlating with higher staff turnover or outdated resources impacting student engagement.

3. Take Action: Implement targeted solutions, like updating classroom technology, adjusting schedules, or providing additional support for teachers.

Code Example for Multimodal Feedback: 

from azure.cognitiveservices.speech import SpeechConfig, SpeechRecognizer 

from azure.ai.textanalytics import TextAnalyticsClient 

from azure.core.credentials import AzureKeyCredential 

speech_config = SpeechConfig(subscription="<your_speech_key>", region="<your_region>") 

recognizer = SpeechRecognizer(speech_config=speech_config) 

print("Listening for feedback...") 

result = recognizer.recognize_once() 

transcription = result.text 

print(f"Transcription: {transcription}") 

# Analyze Sentiment 

endpoint = "<your_text_analytics_endpoint>" 

key = "<your_text_analytics_key>" 

client = TextAnalyticsClient(endpoint=endpoint, credential=AzureKeyCredential(key)) 

response = client.analyze_sentiment(documents=[transcription]) 

for document in response: 

    print(f"Sentiment: {document.sentiment}, Confidence Scores: {document.confidence_scores}") 

Example Outcome:
One school discovered that while teachers’ written feedback highlighted workload issues, their verbal feedback revealed deeper frustrations with inflexible scheduling. By adjusting timetables and providing more planning time, the school saw a 15% improvement in teacher satisfaction and retention.

Why This Matters for Your School

• Support Your Teachers: Happy, supported teachers are more effective in the classroom and more likely to stay long-term.

• Engage Your Students: Modern resources and a positive learning environment boost student motivation and outcomes.

• Build a Stronger Culture: Addressing feedback fosters trust and collaboration among staff, students, and parents.

3. Streamlining Exam Experiences

Exams are a high-pressure time for students, and even small issues—like unclear instructions or tight schedules—can add unnecessary stress. But what if you could identify and address these problems before they impact student performance?

The Challenge: Stressful Exam Experiences

Post-exam surveys often reveal recurring complaints from students:

Example Feedback:

• “The instructions weren’t clear, and I didn’t know what to do.”

• “There wasn’t enough time to complete the paper properly.”

Without a way to analyse this feedback in real time, schools risk repeating the same issues year after year, leaving students frustrated and stressed.

The Solution: Deesha and Azure Stream Analytics

With Deesha, you can collect and analyse feedback during exams using Azure Stream Analytics. This allows you to spot patterns—like confusion over instructions or time management issues—and address them immediately for future sessions.

How It Works:

1. Collect Real-Time Feedback: Gather student feedback during or immediately after exams.

2. Analyse Sentiment: Use Deesha to categorise feedback into positive, neutral, or negative sentiments, identifying key pain points.

3. Take Action: Implement changes, such as clearer instructions, better time allocation, or additional support for students.

SQL Query Example: 

SELECT Feedback,  

       CASE  

           WHEN SentimentScore < 0.4 THEN 'Negative' 

           WHEN SentimentScore BETWEEN 0.4 AND 0.7 THEN 'Neutral' 

           ELSE 'Positive' 

       END AS SentimentCategory 

INTO PowerBIDashboard 

FROM ExamFeedbackStream 

Why This Matters for Your School

• Reduce Student Stress: Clear instructions and fair time limits help students focus on performing their best.

• Improve Exam Outcomes: Addressing feedback leads to better-designed exams and happier, more confident students.

• Build Trust: Proactively improving the exam experience shows students and parents that you value their feedback and are committed to fairness.

Ready to Create a Better Exam Experience?

Deesha makes it easy to turn exam feedback into actionable insights, helping you reduce stress and improve outcomes for your students.

👉 Contact us today to see how Deesha can streamline your school’s exam processes.

4. Empowering Multi-Academy Trusts with Data-Driven Decision Making

Managing and analysing feedback across multiple schools within an MAT presents unique challenges. However, by aggregating and analysing feedback data across the entire network, MAT leaders can gain valuable insights into systemic issues and identify best practices that can be shared across all schools.

Real-World Example:

Imagine a MAT where some schools consistently receive high levels of parent satisfaction, while others report frequent communication gaps. Using NLP to analyse feedback data from all schools within the MAT, leaders can uncover critical variables leading to success in high-performing schools.

Code Example: 

import pandas as pd 

from azure.ai.textanalytics import TextAnalyticsClient 

from azure.core.credentials import AzureKeyCredential 

feedback_data = pd.read_csv("mat_feedback.csv") 

client = TextAnalyticsClient(endpoint="<your_endpoint>", credential=AzureKeyCredential("<your_key>")) 

response = client.analyze_sentiment(documents=feedback_data["Feedback"].tolist()) 

feedback_data["Sentiment"] = [doc.sentiment for doc in response] 

feedback_data.to_csv("analyzed_feedback.csv", index=False) 

Outcome: Insights from this process allow MATs to create tailored action plans, ensuring every school benefits from shared knowledge and resources. 

The Future of Feedback Analysis: What’s Next?

1. Predictive Analytics for Proactive Solutions

Predictive analytics is revolutionising feedback analysis by enabling schools to anticipate and address issues before they escalate. With tools like Azure Machine Learning, schools can forecast trends such as increased student dissatisfaction during exam periods or teacher burnout based on workload feedback.

Implementation Example:

from azureml.core import Workspace, Experiment

# Connect to Azure Machine Learning workspace

ws = Workspace.from_config()

# Create an experiment for predictive feedback analysis

experiment = Experiment(workspace=ws, name="predictive-feedback")

print("Training predictive model...")

Using predictive models, schools can take proactive efforts to promote happiness and well-being, resulting in a better learning environment for everybody.

2. Comparative Feedback Over Time

Analysing feedback year-over-year is essential for measuring the effectiveness of initiatives. Are students more satisfied with resources now than last year? Are teacher workloads improving? Comparative feedback analysis provides actionable insights to answer these questions.

Code Example:

import pandas as pd  

# Load historical and current feedback data  
historical = pd.read_csv("historical_feedback.csv")  
current = pd.read_csv("current_feedback.csv")  

# Combine and analyze data  
combined = pd.concat([historical, current])  
comparison = combined.groupby(["Year", "Category"])["Sentiment"].value_counts()  

print(comparison)  

This approach helps schools track progress, identify trends, and make data-driven decisions to enhance their programs and policies.

3. Multimodal Feedback as the New Standard

In the future, text-based feedback alone won’t be enough. Schools are increasingly adopting multimodal feedback analysis, which includes voice, video, and live chat data. These richer data sources provide deeper insights into student and teacher experiences, enabling schools to address concerns more effectively.

For example, analysing tone and emotion in voice feedback or facial expressions in video responses can uncover nuances that text alone might miss. This holistic approach ensures a more comprehensive understanding of feedback.

Why This Matters for Your School

The future of feedback analysis is here, and it’s powered by advanced technologies like predictive analytics, comparative data analysis, and multimodal feedback. By adopting these tools, schools can:

• Proactively address issues before they become problems.

• Measure the impact of initiatives over time.

• Gain deeper insights from diverse feedback sources.

Stay ahead of the curve by integrating these innovative approaches into your feedback analysis strategy.

Conclusion: Transforming Education with NLP and Azure

Feedback is the cornerstone of progress in education. It holds the power to shape student outcomes, enhance teacher satisfaction, and build stronger relationships with parents. However, without the right tools, this valuable resource can go untapped. Natural Language Processing (NLP) and Microsoft Azure’s advanced suite of tools are revolutionising how schools and MATs analyse and act on feedback, turning insights into actionable strategies for growth.

From streamlining admissions and improving exam experiences to empowering teachers and enabling data-driven decisions across MATs, the possibilities are endless. With predictive analytics, comparative feedback analysis, and multimodal feedback integration, schools can:

• Anticipate challenges before they arise.

• Measure the impact of initiatives over time.

• Uncover deeper insights through voice, video, and text analysis.

The future of education is feedback-driven, and the tools to harness its potential are here. By embracing NLP and Azure, schools can create environments where students thrive, teachers feel supported, and parents are engaged.

Ready to Transform Your School with Deesha?

Don’t let valuable feedback go to waste. With Deesha, powered by NLP and Microsoft Azure, you can:

• Save time by automating feedback analysis.

• Make smarter decisions with actionable insights.

• Build trust by addressing concerns proactively.

The future of education starts with you. Take the first step towards a smarter, more responsive school environment.

👉 Book a free demo today and see how Deesha can transform your feedback analysis process.