Digital Chemistry Laboratory, Student Set, with AI-Powered Digital Course

• Purpose: student laboratory, practical and research work in the chemistry classroom and in other science and mathematics subjects
• Configuration: student set — sensors for acidity, conductivity, temperature, gas pressure and optical properties of solutions, for work at a student desk individually or in a small group
• Number of sensors: 6 (5 types; temperature sensor — 2 pcs)
• Sensor type: wireless, self-contained; a datalogger or other analogue-to-digital converter is not required
• Readout on the sensor: own colour LCD screen, 1.8 in diagonal, showing the current value with its unit at the moment of measurement
• Data transfer: wireless, from several sensors simultaneously, to a computer, mobile device or cloud service, automatically and without manual entry
• Software: displays data as tables and graphs, exports data to spreadsheet editors and other programs
• Interface language: Ukrainian by default, English as an option
• Digital course volume: 70 academic hours
• AI assistant: integrated into the platform, built on retrieval-augmented generation
• Licence (access right) term: 12 months

Kit Contents:

Wireless Sensors

1. Temperature sensor
   • Range: from minus 50 to plus 200 °C
   • Resolution: 0.01 °C
   • Qty: 2 pcs
2. Water quality (pH) sensor
   • Range: 0–14 pH
   • Resolution: 0.01 pH unit
   • Qty: 1 pc
3. Conductivity sensor
   • Range: 0–20 000 µS/cm
   • Resolution: 1 µS/cm
   • Qty: 1 pc
4. Gas pressure sensor with syringe
   • Range: 0–700 kPa
   • Resolution: 0.1 kPa
   • Qty: 1 pc
5. Colorimeter sensor
   • Range: 0–100 %
   • Resolution: 0.01 %
   • Qty: 1 pc

Storage, Documentation and Software

• Storage box with moulded tray inserts for storing and carrying the sensors — 1 pc
• Operation manual and methodological guide for experiments, laboratory work and project activities — 1 set
• Software, Ukrainian interface, compatible with the operating system of the device used by the education institution: data as tables and graphs, export to spreadsheet editors and other programs; English interface available as an option — 1 pc
• Access to the digital course on the learning management system, 70 academic hours — 1 pc
• Access to the AI assistant integrated into the learning management system — 1 pc
• Licence (access right) to the software and materials, 12 months — 1 pc

The digital learning materials and the AI assistant are an integral part of the set and are supplied with it; access is provided on the edu.unowa.eu platform.

Product passport: sens-bundle-с-st-ua (PDF)

The AI assistant is a separate tool of the digital course, integrated into the learning management system and built on retrieval-augmented generation: it forms its answers from a localised knowledge base aligned with the national curriculum of Ukraine. Data from the sensors reaches the platform automatically, without manual entry, so full-scale digital investigations can be run and analysed there.

AI Assistant Functions

• Task selection: automated selection of research tasks and experiments matching the topic of the lesson
• Methodological support: step-by-step description of the procedure for conducting experimental research
• Error analysis: identification of typical student errors and personalised recommendations for correcting them
• Adaptive difficulty: adaptation of task difficulty to different levels of student preparation
• Reports and conclusions: support in compiling reports on research results and in structuring the conclusions drawn from experiments
• Knowledge base: operation on a localised knowledge base aligned with the national curriculum of Ukraine
• Licence: right of access to the software and materials valid for 12 months
• Language: content, interface and learning materials in Ukrainian

Work with experimental data

• Visualisation: presents the measured values as graphs and tables
• Analysis: analyses the results obtained in the experiment
• Patterns: identifies the relationships observed during the experiment
• Reference comparison: compares the measured data with reference values
• Interpretation: helps students form hypotheses, conclusions and interpretations within a defined 'knowledge corridor'