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Digital for Active Education Overview

Active Learning Approach

Students are creators engaging with digital tools and inquiry-driven STEAM methodologies, not passive learners.

Strategic Pillars

The program focuses on digital literacy, inclusion, and sustainability to address diverse learners and real-world challenges.

Teacher Professional Development

Workshops immerse educators in active learning, enabling them to effectively use digital tools and facilitation strategies.

Consortium Collaboration

The partnership includes universities and schools from multiple European countries sharing methodologies and pilot programs.

�Digital for Active Education (Dig4AEdu) is an Erasmus+ Key Action 2 cooperation partnership created to modernize STEAM education by strengthening digital innovation and active learning practices across European schools. The approach positions students not as passive recipients but as creators capable of engaging with digital tools, physical computing, and inquiry-driven methodologies. The program emphasizes three strategic pillars—digital literacy, inclusion, and sustainability—to ensure that educational transformation reaches diverse learners and connects classroom learning to real-world challenges. At the heart of this initiative is a consortium linking universities and schools from Portugal, Romania, Latvia, Greece, and Türkiye. Through coordinated professional development, classroom pilots, and shared methodological frameworks, participating educators gain access to common training structures, hands-on activities, and pedagogically sound approaches designed for immediate classroom use. Their experiences in workshops and practical laboratory-style sessions reflect a growing European demand for educators who can confidently integrate tools such as micro:bits, Arduino boards, sensors, and simulations in fostering student-driven inquiry. These workshops do more than provide technical demonstrations; they immerse teachers in active learning environments, allowing them to practice the same facilitation strategies expected of their students. By adopting UPORTO-led training methods, educators experience firsthand the power of curiosity-based learning, iterative building and testing, and evidence‑based reasoning. As a result, teachers can better understand how digital tools bridge abstract concepts with tangible experimentation, ultimately supporting student engagement, deeper understanding, and long-term skill development across STEAM domains.

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Project Foundations and Pedagogical Shifts

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What Dig4AEdu Is Building

Enhancing STEAM Education

Dig4AEdu empowers teachers to deliver STEAM learning focused on digital literacy, creativity, and real-world problem solving.

Collaborative European Network

The project aligns training and implementation across partner countries to create a unified educational framework.

Inclusive and Adaptive Learning

Dig4AEdu offers adaptable hardware and accessible coding environments to support diverse student needs.

Sustainability in Education

Teachers incorporate environmental awareness into digital projects emphasizing sustainable materials and impact.

�Dig4AEdu focuses on equipping European schools with the structures, tools, and pedagogical strategies necessary for an era of active, digitally infused learning. Recognizing the accelerating pace of technological change, the project strengthens the capacity of teachers to design and deliver STEAM learning experiences grounded in digital literacy, creativity, and real-world problem-solving. The initiative supports the development of classroom-ready methodologies, digital toolkits, and learning pathways that emphasize technology‑enhanced inquiry and physical computing. Central to this effort is the alignment of activities across partner countries including Portugal, Romania, Latvia, Greece, and Türkiye, enabling a coherent training and implementation framework. By connecting universities and schools, the project fosters a community of practice where educators share outcomes, refine teaching strategies, and pilot digital innovations directly with learners. The focus on inclusion ensures that diverse student groups benefit from these advancements by offering adaptable hardware, differentiated challenges, and accessible coding environments. Sustainability remains a core theme as teachers learn to frame digital projects within environmentally conscious contexts, from material selection to long-term societal impact. Ultimately, Dig4AEdu’s project context highlights a commitment to empowering schools with the competencies and resources required to integrate digital creativity and active learning into everyday classroom practice.

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The Big Shift in Teaching Through UPORTO-Led Training

Inquiry-Based Learning Mindset

UPORTO training redefines inquiry as a mindset, shifting teachers from transmitters to facilitators encouraging curiosity and exploration.

Hands-On and Heads-On Approach

The training highlights blending hands-on activities with critical thinking to deepen student engagement and skill development.

Developing Essential Competencies

This model fosters collaboration, critical thinking, persistence, and authentic problem-solving in a dynamic STEAM learning environment.

�UPORTO-led training emphasized a foundational transformation in how teachers view inquiry-based learning (IBL), making it clear that inquiry is not a specific activity type but rather a pedagogical mindset. This shift redefines the teacher’s role from knowledge transmitter to learning facilitator, encouraging students to ask questions, explore possibilities, and articulate reasoning. In this model, learning begins with curiosity, not answers. Teachers guide through probing questions, scaffolds, and structured reflection rather than pre‑packaged explanations. The training highlighted the importance of blending hands-on engagement—such as building, testing, and measuring—with heads-on thinking that involves reasoning, interpretation, and communication. This dual approach strengthens student ownership and develops essential competencies including collaboration, critical thinking, and scientific reasoning. One major takeaway is that inquiry-based learning promotes deeper engagement and more authentic problem-solving compared to traditional instructional formats. The workshops demonstrated that shifting to a questions-first culture helps students develop persistence and independence while still enabling teachers to maintain structure and purposeful facilitation. The methodology supports a more dynamic classroom where learners actively test hypotheses, iterate designs, and reflect on outcomes, cultivating both conceptual understanding and transferable skills needed for STEAM disciplines.

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Inquiry-Based Learning and Instructional Models

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Why Inquiry-Based Learning Works

Active Learning Through Inquiry

IBL promotes active student engagement by encouraging problem-solving and investigation to construct understanding.

Accessible to Diverse Learners

With proper scaffolding and clear structure, inquiry learning benefits students of all performance levels and backgrounds.

Development of Critical Skills

Inquiry builds resilience, curiosity, and reflective thinking essential for academic success and real-world STEM applications.

�Inquiry-Based Learning (IBL) operates on the premise that students learn more effectively when they actively construct understanding through problem-solving, investigation, and iterative experimentation. Rather than starting from explanations, IBL begins with meaningful problems or questions that prompt learners to explore ideas and test possibilities. This approach supports the development of autonomous learning behaviours, as students plan investigations, gather evidence, revise thinking, and justify conclusions. During the UPORTO training, educators examined how hands-on investigations and systematic thinking—including planning experiments, recording data, and refining procedures—enable students to deepen conceptual mastery. A common misconception addressed in the training is the belief that inquiry works only for high-performing students. Instead, evidence shows that with appropriate scaffolding, incremental challenge, and clear structure, inquiry is accessible and beneficial for diverse learners. Teachers learned strategies for making abstract ideas more concrete through manipulatives, measurable phenomena, and sensor‑based data collection. By centering instruction on observable concepts and authentic questions, educators can support varied readiness levels while still promoting high engagement. Inquiry’s strength lies in building resilience, curiosity, and reflective thinking—competencies essential for long-term academic success and transferable to real-world STEM applications.

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Learning Theories and Structured Inquiry

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Coherence Through Learning Theory

Behaviorist Foundations

Inquiry learning leverages reinforcement, modeling, and feedback to help students master foundational skills effectively.

Cognitivist Principles

Activating prior knowledge and using metacognitive strategies reduce cognitive load and enhance learner understanding.

Constructivist Alignment

Learners build knowledge through guided interaction and reflection, with teachers facilitating rather than delivering content.

Social Constructivism and ZPD

Collaborative problem-solving and guided support extend learning beyond individual capabilities in the Zone of Proximal Development.

�The UPORTO-led training connected Inquiry-Based Learning to major educational theories, helping teachers understand why the methodology supports deeper and more durable learning across varied student populations. From a behaviorist standpoint, inquiry benefits from structured reinforcement, modeling, and timely feedback, especially when students are first mastering foundational techniques. Cognitivist principles emphasize the importance of activating prior knowledge, reducing unnecessary cognitive load, and helping learners develop metacognitive strategies to monitor and adjust their thinking. Constructivism provides perhaps the strongest alignment with inquiry, asserting that learners build understanding through purposeful interaction with phenomena; in this model, the teacher becomes a facilitator who guides reflection and supports meaning-making rather than simply delivering information. Social constructivism, particularly Vygotsky’s Zone of Proximal Development (ZPD), underscores the value of collaborative investigations, group problem‑solving, and guided support to extend learning beyond what students could achieve independently. By linking inquiry practices to these theoretical foundations, the training equipped educators with a language and rationale for explaining instructional decisions, anticipating learner challenges, and designing lessons that integrate motivation, cognitive structure, and social interaction for optimal student growth.

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UPORTO’s Practical Inquiry Framework

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5E Instructional Model as the Core

Engage Phase

Teachers activate prior knowledge and spark curiosity using authentic problem contexts.

Explore and Explain

Students investigate with guidance; then articulate findings to build key knowledge.

Elaborate and Evaluate

Learners apply concepts to new situations while demonstrating understanding through reflection and tasks.

Extensions and Digital Tools

Model includes peer exchange and empowerment, enhanced by tools like micro:bits and Arduino.

�The training positioned Bybee’s 5E instructional model—Engage, Explore, Explain, Elaborate, Evaluate—as a practical backbone for designing inquiry‑driven lessons. In the Engage phase, teachers surface students’ prior conceptions and spark curiosity using authentic problem contexts. During Explore, students plan and carry out investigations while teachers guide through questioning rather than direct instruction. In the Explain phase, learners articulate their findings, and teachers help formalize key knowledge that students may not derive independently. The Elaborate stage encourages application of concepts to new situations, gradually increasing complexity and promoting transfer of learning. Evaluation occurs continuously as students demonstrate understanding through evidence, reflection, presentations, or performance tasks. Extensions discussed during training included Exchange—sharing learning with peers or the community—and Empowerment—encouraging action based on new understanding, especially in sustainability‑focused contexts. The 5E model offers teachers a clear, repeatable structure that integrates scientific reasoning, autonomy, and communication, making it especially effective when paired with digital tools like micro:bits and Arduino. Ultimately, the framework helps educators design coherent learning cycles that balance exploration with structure.

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Teacher Decision-Making and Facilitation

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Inquiry Facilitation Routines

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Practical Moves That Make Inquiry Work

Using Open-Ended Questions

Open-ended questions stimulate divergent thinking and encourage students to explore possibilities deeply.

Providing Adequate Wait Time

Allowing students time to think leads to deeper responses and reduces dependence on teacher cues.

Neutral Paraphrasing

Paraphrasing student ideas without immediate evaluation helps maintain student reasoning ownership.

Structured Inquiry Environment

Clear expectations and discipline ensure inquiry remains productive and focused on meaningful learning.

�Effective inquiry-based teaching requires intentional facilitation strategies that support student thinking without reducing autonomy. The training emphasized using open-ended questions such as “What do you think would happen if…?” to stimulate divergent thinking. Providing adequate wait time after posing questions helps students formulate deeper responses and reduces reliance on teacher cues. Teachers were encouraged to paraphrase student ideas neutrally rather than evaluating immediately, allowing students to maintain ownership of their reasoning. Small, manageable shifts can significantly strengthen inquiry, such as removing pre‑made data tables so students decide what variables to record, or providing only partial procedures so learners attempt problem‑solving before formal explanation. Importantly, inquiry should not be mistaken for unstructured free time—classroom discipline and clear expectations are essential for productive exploration. By incorporating these facilitation routines, teachers create an environment where students feel safe to experiment, take intellectual risks, and iterate on ideas, all while maintaining the structured support needed for meaningful learning.

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Digital Learning Through Physical Computing

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Tools for Classroom Prototyping

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micro:bit for Rapid Prototyping

Integrated Hardware Features

micro:bit includes LED matrix, buttons, sensors, microphone, and speaker enabling instant interactive experiments without extra parts.

Wireless Communication

Bluetooth Low Energy connectivity allows for wireless collaboration and communication between devices.

Programming Flexibility

Supports beginner-friendly block coding via MakeCode and advanced Python programming for complex projects.

Educational Impact

Encourages quick prototype cycles, boosts student confidence, and fosters computational thinking and problem-solving skills.

�The micro:bit was presented as an ideal platform for rapid prototyping due to its built-in features that require minimal setup, enabling teachers and students to achieve early success. Its integrated 5×5 LED matrix, input buttons, accelerometer, magnetometer, microphone, and speaker offer immediate opportunities for interactive experimentation without additional hardware. Bluetooth Low Energy (BLE) connectivity also allows for wireless communication and collaborative projects. Programming can be introduced through block-based MakeCode, which supports beginners, or advanced through Python for extending complexity. The micro:bit encourages quick test–debug–improve cycles, making it especially suitable for workshops with limited time or resources. Because even simple projects feel interactive and rewarding, the device builds student confidence while providing a solid foundation for exploring computational logic, algorithms, and problem‑solving. The training highlighted that micro:bit’s accessibility and versatility make it an excellent entry point for physical computing and inquiry‑based exploration.

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Advanced Engineering Exploration

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Arduino for Deep Electronics Learning

Arduino in Education

Arduino is a powerful open-source platform ideal for teaching advanced electronics and engineering concepts.

Coding and Simulation

Beginners use block-based coding and simulations, while advanced learners program in C/C++ via Arduino IDE.

Hands-on Engineering Practice

Arduino projects develop skills in wiring, component selection, signal protocols, and calibration through iterative testing.

Advanced Integration and Design

Arduino supports precise data acquisition and multi-component integration, advancing engineering design skills.

�Arduino was highlighted as a powerful open‑source platform well‑suited for educators aiming to introduce students to deeper engineering and electronics. Widely used in educational and maker communities, Arduino supports the exploration of circuits, sensors, actuators, and modular system design. Learners engage with industry‑aligned coding through the Arduino IDE using C/C++, while beginners can use Tinkercad Circuits for block‑based coding and virtual simulations. This dual‑path approach offers accessibility without sacrificing rigor. Arduino projects require learners to manage wiring, component selection, signal protocols, and calibration, promoting authentic engineering practices. Through iterative testing and debugging, students develop strong problem-solving skills and learn the practical realities of electronic systems, including noise, thresholds, and hardware limitations. Arduino shines in projects requiring precise data acquisition or multi-component integration, making it a critical next step after micro:bit for classes ready to deepen reasoning, technical skill, and engineering design capabilities.

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Sensors and Evidence-Based Learning

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Why Sensors Matter

Role of Sensors in Learning

Sensors enable students to gather authentic data and test hypotheses through measurable evidence.

Transforming Abstract to Observable

Sensors convert abstract scientific models into observable patterns using graphs and error analysis.

Building Scientific Competencies

Interpreting sensor data fosters skills such as data literacy, computational thinking, and troubleshooting.

Structured Documentation Importance

Documentation practices like tables, labeled graphs, and reflection help students justify claims scientifically.

�Sensors play a crucial role in bridging student curiosity with measurable, evidence‑based learning. Whether measuring distance, light, temperature, moisture, or motion, sensors allow students to collect authentic data and test hypotheses using quantifiable evidence. They help transform abstract models into observable patterns through graphs, thresholds, and error analysis. By analyzing variability and interpreting sensor readings, students build essential competencies such as data literacy, computational thinking, and systematic troubleshooting. The training emphasized the importance of pairing sensor-based investigation with structured documentation practices, including organized data tables, labeled graphs, explanation writing, and reflective presentations. This approach encourages students to connect their findings to scientific concepts, justifying claims with measurements rather than opinions. Sensors not only make inquiry tangible but also introduce students to the real-world processes scientists and engineers use. As learners iterate on their builds, adjust thresholds, and refine mechanisms, they gain hands-on experience with both hardware and analytical reasoning, strengthening overall scientific understanding.

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Workshop Pedagogical Structures

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Simulation, Building, Testing, Presenting

Simulation Phase

Simulation allows students to visualize and test circuits using digital platforms, reducing material limitations and risks.

Physical Building

Students build physical devices using breadboards, sensors, actuators, and microcontrollers after completing simulations.

Testing and Iteration

Testing involves calibrating devices and troubleshooting wiring, with iteration refining functionality and logic.

Presenting Results

Students communicate their design process, data, and improvements, mirroring professional engineering workflows.

�A recurring methodology across Dig4AEdu workshops involves a clear workflow: simulation, build, test, iterate, and present. Teachers first guide students through simulations using platforms such as Tinkercad, allowing them to visualize circuits, test logic, and reduce material constraints. This simulation phase minimizes risk and supports accessibility when hardware availability is limited. After simulation, students transition to physical building using breadboards, jumper wires, sensors, actuators, and microcontrollers such as micro:bit or Arduino. Testing and calibration follow, requiring learners to adjust thresholds, refine mechanical alignment, and address sensor noise or code errors. Iteration becomes a natural part of the process as students troubleshoot wiring, modify logic, and refine functionality. The workflow concludes with communication, where students demonstrate their device, explain decisions, present data, and articulate challenges and improvements. This aligned structure mirrors professional engineering and scientific inquiry, fits within school constraints, and ensures students experience the full design–test–communicate cycle essential for STEM competency development.

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Classroom Output Examples

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Ion Roulette Wheel with micro:bit

Eco-Friendly Design

The Ion Roulette Wheel uses recycled materials promoting sustainability in educational projects.

Chemistry Integration

The project teaches ionic compounds concepts like cations, anions, and charge balancing interactively.

Computational Thinking

Random selection algorithms synchronize code with the physical wheel movement for engagement.

Design and Collaboration

Students applied design thinking through material selection and teamwork to create a functional tool.

�One featured classroom example involved building an eco‑friendly Ion Roulette Wheel using a micro:bit, a servo motor, and recycled materials. The activity was framed through an inquiry prompt such as, “How can we build a sustainable tool that helps us learn about ionic compounds and technology?” This project integrated chemistry concepts—including cations, anions, charge balancing, and formula writing—with computational thinking through random selection algorithms and synchronization between code and physical wheel movement. Students engaged in design thinking by selecting materials, constructing a stable mechanism, and ensuring usability. The assessment emphasized teamwork, precise formula notation, critical thinking, and the ability to explain how the device functioned. This example illustrates how digital tools can support interdisciplinary learning, making chemistry concepts interactive while reinforcing code‑based reasoning and sustainable design practices.

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Arduino and micro:bit Applied Projects

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Arduino Automatic Door System

Sensor and Actuator Use

The system uses an ultrasonic sensor to detect proximity and a servo motor to open or close the door automatically.

Real-time Data Interpretation

Students learned to interpret sensor data in real time and implement conditional logic for responsive door control.

Engineering Iteration

The project involved tuning distances, servo angles, and timing through iterative testing for optimal performance.

Motivation and Learning

The hands-on project increased motivation by demonstrating cause and effect in everyday automation systems.

�The Arduino Automatic Door System served as a flagship example demonstrating real-world application of sensors and actuators. Students constructed an automated entry system similar to those used in shops or hotels, utilizing an ultrasonic sensor to detect proximity, a servo motor to open or close the door, and LEDs or a buzzer to signal states. Through this project, learners interpreted sensor data in real time, implemented conditional logic to generate appropriate responses, and optimized thresholds for reliability. The activity highlighted the iterative nature of engineering as students tuned distances, servo angles, and timing based on trial outcomes. This authentic scenario increased motivation by helping students see immediate cause‑and‑effect relationships and understand how automation functions in everyday environments.

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Further Applied Physical Computing

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micro:bit Ultrasonic Alarm System

Project Focus and Purpose

The project emphasized safety and cultural relevance through designing distance-based ultrasonic alarm systems for diverse uses.

Hardware Components Used

Students utilized micro:bit, expansion board, ultrasonic sensor, LCD display, and LED or audio alerts to create alarms.

Learning and Skills Development

Learners honed troubleshooting, sensor calibration, communication, and critical thinking skills through hands-on hardware testing.

Applied Problem-Solving

Moving from simulation to physical hardware built confidence, resilience, and systematic debugging abilities in students.

�The micro:bit Ultrasonic Alarm project emphasized safety, accessibility, and cultural relevance by inviting students to design a distance‑based warning system useful for protecting heritage objects, securing restricted areas, or improving pedestrian safety. Students used a micro:bit with an expansion board, an ultrasonic sensor, an LCD display, and LED or audio alerts to create differentiated warning signals based on distance thresholds. The project required learners to adjust sensor sensitivity, troubleshoot wiring, interpret feedback, and test performance under different conditions. By presenting their systems and explaining calibration methods, students strengthened communication and critical thinking skills. Moving from simulation to physical hardware improved confidence and resilience, demonstrating the value of applied problem-solving and systematic debugging in real-world design challenges.

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Data Literacy and Decision-Making

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From Sensor Readings to Graphs

Sensor Data Collection

Students connected sensors to Arduino boards to collect real-time data streamed into spreadsheets and charting tools.

Data Visualization and Patterns

Visualization helped identify patterns, trends, and anomalies supporting evidence-based decision-making.

Applying Conditional Logic

Conditional logic triggered responses like LEDs based on data states such as hot, cold, or fine.

Building Data Literacy Skills

Recording and analyzing data strengthened scientific reasoning, coding logic, and engineering design skills.

�The data and measurement workshop highlighted the importance of transforming sensor readings into meaningful insights through visualization and interpretation. Students connected temperature or other sensors to Arduino boards and streamed data into spreadsheets or live charting tools. They identified patterns, monitored trends, and detected anomalies or sudden value changes. These observations supported evidence-based decision-making, such as triggering LEDs, adjusting thresholds, or applying conditional logic to determine states like “hot,” “cold,” or “fine.” The process developed students’ ability to design experiments thoughtfully, understand variability, and communicate conclusions supported by evidence rather than intuition. By recording, graphing, and analyzing data, learners strengthened data literacy—a key 21st-century competency—with direct connections to scientific reasoning, coding logic, and engineering design.

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Inclusion and Access in Digital Learning

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Making Physical Computing Work for All

Inclusive Programming Tools

Using visual programming tools reduces syntax barriers and encourages broad student participation in coding activities.

Team Role Diversity

Assigning varied team roles enables students with different strengths to contribute meaningfully in physical computing projects.

Differentiated Challenges

Offering challenge levels from simple LED projects to multi-sensor systems helps students engage at their own pace.

Accessible Hardware Adaptations

Hardware modifications like larger inputs, clear labels, and scaffolded instructions support accessibility for all learners.

�The training addressed inclusion and accessibility explicitly, ensuring that physical computing and inquiry-based methods benefit all students. Teachers explored strategies such as using visual programming tools (MakeCode, Scratch, Tinkercad Blocks) to lower syntax barriers and broaden participation. Roles within teams were varied—coding, wiring, documenting, testing, presenting—to allow students with different strengths to contribute meaningfully. Differentiated challenge levels enabled students to engage at an appropriate pace, starting with simple LED-based projects and progressing to multi-sensor systems. Hardware adaptations included larger input devices, clear labeling, structured checklists, and scaffolded instructions. When resources were limited, teachers implemented rotation systems, sharing protocols, and simulation-first approaches to ensure equitable access. These practices help create inclusive classrooms where all learners can participate in authentic STEM experiences.

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Troubleshooting and Classroom Realities

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Challenges Teachers Should Anticipate

Resource Constraints Impact

Limited hardware and sensors can affect pacing and group size in physical computing lessons.

Teacher Preparedness Variability

Educators' confidence in electronics, coding, and debugging varies and needs ongoing support.

Common Technical Issues

Troubleshooting wiring, connection, sensor and logic errors is routine and essential to learning.

Proactive Teaching Practices

Testing parts individually, safety routines, organized workspace, and supervision improve learning.

�The training prepared educators to anticipate common challenges in implementing physical computing and inquiry-based learning. Resource constraints—such as limited hardware, insufficient sensors, or restricted access to devices—can impact pacing and group size. Teacher preparedness also plays a role; confidence with electronics, coding, and debugging varies widely and often requires ongoing professional learning and peer support networks. Technical issues are routine, including wiring mistakes, connection problems, inconsistent sensor readings, and logic bugs. Educators were encouraged to normalize troubleshooting as an integral part of learning, fostering resilience and systematic thinking in students. Recommended practices included testing components individually before integrating them, maintaining clear safety routines, keeping an organized workspace, and supervising tool use responsibly. By anticipating barriers and implementing proactive strategies, teachers can maintain productive learning environments and model real-world problem-solving.

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Summary and Transfer to Schools

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Key Outcomes to Take Back to School

Student Product Components

Student projects integrate sensing, measuring, and responding using micro:bit or Arduino with sensors and actuators.

Inquiry Documentation

Structured documentation includes tables, graphs, design notes, and justified claims based on measurements.

Skill Development Focus

Activities promote growth in computational thinking, problem-solving, collaboration, communication, and creativity.

Progression Pathways

Training progresses from micro:bit prototyping to Arduino for advanced engineering challenges.

�By the end of the UPORTO-led training sequence, teachers gained a clear understanding of what strong Dig4AEdu‑aligned workshops and practical sessions should produce. High-quality student products incorporate sensing, measuring, and responding components using micro:bit or Arduino platforms paired with sensors and actuators. Inquiry evidence includes structured documentation—tables, graphs, design notes, and justified claims grounded in collected measurements. Classroom activities are designed to cultivate visible skill growth across computational thinking, problem-solving, collaboration, communication, and creativity. Strong workshop design also ensures real-world relevance, connecting classroom learning to sustainability, community well-being, safety, or technological efficiency. Teachers gained insight into progression pathways, beginning with micro:bit for rapid prototyping and confidence building, then advancing to Arduino for more complex engineering challenges. These outcomes equip educators with practical tools, pedagogical strategies, and confidence to implement digital active learning effectively within their home schools.