Innovation / PHL Classroom

Where scientific curiosity becomes discovery.

Bring environmental science and applied data intelligence into the classroom. Investigate real-world questions, collect evidence, develop algorithms and learn to interpret the results together.

Teacher and students exploring environmental observations using the Classroom Engine

The scientific classroom process

Collect evidence. Build intelligence. Discover insights.

PHL Classroom connects scientific investigation with data-driven learning, from the first observation to testing an algorithm.

01

Data collection

Capture observations using virtual or supported physical sensors, label specimens and develop a scientific dataset.

Observe · Capture · Label
02

Algorithm development

Organise labelled evidence, configure training and develop classification or regression models.

Configure · Train · Evaluate
03

Predictions & inference

Test trained models against new observations, interpret their outputs and consider uncertainty.

Predict · Interpret · Refine
↻   Interpret results · Refine the investigation · Repeat
Virtual Laboratory

Your classroom.
Your laboratory.
No hardware required.

Experience PHL Classroom using virtual sensors. Collect simulated observations, label specimens, develop algorithms and explore inference before investing in physical sensing equipment.

Real workflows

Explore scientific processes used with supported sensors.

Simulated observations

Investigate changing environmental sensor data.

No hardware needed

Begin with the available Education Trial capabilities.

Trial capabilities and specimen limits apply. Simulated measurements are not physical observations.

PHL Classroom Engine Virtual Lab showing simulated sensor capture and scientific signal visualisations on a laptop

PHL Classroom Engine Virtual Lab — simulated environmental sensor observations.

Choose a scenario

Explore supported simulated environmental conditions.

Collect simulated data

Observe sensor signals through the capture workflow.

Label specimens

Organise observations using scientific specimen definitions.

Develop and test

Explore training and inference where entitled.

1 Ask a question

Define an investigation.

2 Choose a scenario

Select a simulated environment.

3 Collect data

Capture simulated readings.

4 Label specimens

Build labelled observations.

5 Develop algorithms

Train models where available.

6 Explore inference

Evaluate predictions and evidence.

Beyond the experiment

One classroom. Connected learning.

Bring educators and students together through organised groups, scientific communication, structured activities and connected learning experiences.

Classroom organisation

Organise students. Build teams. Investigate together.

Create digital classrooms, organise student groups and bring collaborative scientific investigations into one connected learning environment.

PHL Classroom illustration showing teacher-managed student investigation groups

Feature availability depends on the institution's package, entitlement and applicable permissions.

Intelligence throughout the investigation

Your scientific companion. From question to discovery.

Explore how PHL Classroom supports scientific projects, specimen investigations, collection assessment and evidence-based reasoning. Assistance supports student judgement rather than replacing it.

Project guidance

Build a stronger scientific investigation.

Use structured project evidence and readiness guidance to explore investigation goals, identify gaps and develop meaningful scientific reports.

Project evidence
  • Project definition and investigation context
  • Structured scientific report sections
  • Missing-evidence guidance and recommendations

AI assistance is subject to applicable product entitlements and permissions. Assessments provide guidance, not independent scientific validation.

One connected learning environment

Teach science by doing science.

PHL Classroom connects teacher-led activities, student investigations, environmental observations and data analysis. Scientific evidence becomes something students can question, explore and use to develop their own understanding.

For educators

Design the investigation.

Create digital classrooms, organise student groups, define learning activities and guide investigations with structured tasks and outcomes.

For students

Discover through evidence.

Explore specimens, collect labelled observations, investigate patterns, test predictions and communicate findings within the learning experience.

Classroom Engine Calendar showing planned learning activities

For educators

Organise investigations and classroom activity

Support structured scientific learning through classroom scheduling, planned activities and coordinated investigations.

The scientific learning journey

From investigation to understanding.

A connected process that brings experimental science and computational thinking into the same learning journey.

01

Investigate

Frame a scientific question and plan an investigation.

02

Collect

Gather and label observations from specimens and environments.

03

Develop algorithms

Use collected evidence to train and evaluate models.

04

Predict

Apply algorithms to new observations and examine inference results.

05

Interpret

Examine patterns, accuracy and uncertainty in the evidence.

06

Collaborate

Discuss results, share findings and refine scientific understanding.

Virtual and physical investigations

Explore first. Experiment further.

The virtual learning experience allows students to work with simulated sensor observations and explore data-driven investigation without first requiring physical hardware. Supported physical sensing extends the experience into practical specimen and environmental measurements.

Virtual Sensor

Learn without a hardware prerequisite.

Explore simulated observations, specimen labelling, algorithm development and inference within the capabilities available to the account.

Physical sensing

Connect learning to real environments.

Collect supported measurements from physical sensors, investigate specimens and compare observations across experimental conditions.

Available capabilities, usage limits and hardware access depend on the selected package or trial entitlement.

Learning across environments

Real questions. Meaningful evidence.

Investigations can explore soil, controlled environments, specimen headspace and other supported experimental contexts. Students learn to distinguish observations from conclusions and to evaluate what their data can and cannot demonstrate.

Environmental science

Explore changing conditions and compare experimental samples.

Data literacy

Understand labelled datasets, visualisations and evidence quality.

Applied AI

Train, test and critically evaluate predictive algorithms.

For schools, colleges and universities

A platform for inquiry-led learning.

PHL Classroom brings experimental investigation and computational analysis into a coherent educational workflow. Educators can structure activities while students engage with evidence, collaboration and scientific reasoning.

Begin your Classroom journey

Bring scientific discovery into your classroom.

Explore the available Classroom packages and trial options through the Palmer-Hunter Labs platform.