Work Package 3 enables USAGE-NGs to empower smallholder farmers impacted by climate change to adopt digital agricultural technologies for monitoring, quantifying, and mitigating its effects, while fostering sustainable, environmentally friendly, and data-driven farming skills through innovative educational pathways like micro-credentials. Building on existing smart farming and IoT modules at TUM, the project will review and enhance content to meet smallholders’ needs, offering flexible, modular learning that can be combined and recognized across systems to form larger qualifications. The micro-credential framework will align with the European Qualifications Framework (EQF) and partner institutions’ standards, ensuring academic credit, transparency, and recognition across levels 5–8 with a workload of 5–6 ECTS.
Activity 3.1 – Research on relevant training offers, short courses (NQF Lvl 6-8)
A collection of research on training offers that concern climate change including potential for micro-credentials and all partners will provide relevant courses. It will provide information on relevant training offers, just in time solutions to empower smallholder farmers affected by climate change to use digital agricultural technologies to monitor, quantify and mitigate the impacts of climate change on their individual farms.
The report describing qualitative and quantitative results of desktop research on training offers and short courses with micro-credential development potential is being compiled. Survey data from 89 requests sent to 84 Higher Education Institutions (HEIs) in 11 countries provided information on 70 programs at EQF levels 5-8, including blended learning dominating delivery, local language preference, and topics related to climate change and sustainability.
Activity 3.1 of the USAGE-NG project provides a structured mapping of current European education and training offers in smart farming, AgTech, and climate-smart sustainable agriculture at EQF levels 6–8. The report responds to the accelerating pressures of climate change and digital transformation in farming by establishing a benchmark of existing formal degree programs, non- formal professional courses, and informal online learning opportunities.
Using a combination of institutional surveys (25 higher education institutions across 10 countries), qualitative curriculum analysis, and a module matrix covering 189 relevant course modules, the study identifies dominant thematic priorities and pedagogical patterns. The findings show that sustainability and precision agriculture technologies are the most prevalent focus areas, while climate change is typically integrated as a cross-cutting element rather than treated as a standalone specialization.
Most programs rely on blended delivery with strong in-person components, with fully online provision still rare in formal higher education. Traditional teaching methods (lectures and seminars) dominate, complemented by project work and case studies, while more innovative approaches such as flipped classrooms remain uncommon. Competence development emphasizes critical awareness, problem-solving, and managing complexity over narrow technical specialization, reflecting the interdisciplinary demands of modern sustainable farming systems. Overall, the report concludes that Europe’s smart farming education landscape is rich but leaves room for innovation, particularly in strengthening explicit climate adaptation content, expanding learner-centered pedagogies, and supporting flexible, credit -bearing micro-credentials for lifelong learners. These insights directly inform the next steps of USAGE-NG module development and pilot training implementation.
Activity 3.2 – Modules development:Modules development
As part of the we will create courses for smart solutions in agriculture as a response to climate change that will enable diverse students of agricultural sectors including small farmers to use knowledge of the latest developments in smart farming technologies and to enable them to decide which of these technologies are suitable to ameliorate their own situation.
Based on survey results, discussions, and expert input, a “train-the-trainer” strategy (vector system) is considered more reasonable for long-term education than directly training small-scale farmers. As a short-term solution, MOOCs for farmers can be developed. An offline course about innovations and use cases of smart farming technologies is being developed, covering topics like drones, GNSS, sensors, field robotics, IoT, UI, and UX in agriculture. A hybrid course covering similar topics was conducted, and both courses will be evaluated to determine preferences for online/offline teaching. The most suitable topics for MOOCs will be determined, and a first MOOC will be developed and tested.
Activity 3.2 focused on the development of modular learning units and curriculum guidelines for Smart Farming education, applying a micro-credential approach in line with Erasmus+ priorities on digital education, lifelong learning and green transition. Building on the needs identified in Activity 3.1, this activity translated research-based insights into structured, practice-oriented and transferable educational concepts.
The development process was strongly informed by two academic studies conducted within the project as well as by pilot teaching activities implemented in Activity 4.3. This ensured that the developed modules and curriculum guidelines are evidence-based, learner-centred, flexible and suitable for integration into higher education and lifelong learning programmes.
This bachelor’s thesis addresses the design and evaluation of a digital continuing education
format in the field of smart farming for adult education. The aim of the study is to investigate
the effectiveness and acceptance of a short video-based teaching unit as part of a hypo-
thetical Massive Open Online Course (MOOC) on smart farming. The content focuses on
an introduction to GNSS technology as a key component of precision agriculture. The study
examines several research questions: To what extent are the conveyed contents under-
standable for adult learners? How is the online format perceived? Is there interest in further
digital continuing education opportunities in the field of smart farming, and under which
conditions?
Agriculture faces the challenge of feeding a global population growing toward 10
billion people by further increasing its productivity while at the same time operating
in a significantly more sustainable manner in the face of climate change, resource
scarcity, and environmental pollution. Smart farming can make an important
contribution to overcoming these challenges, as digital technologies and data-
based decision support enable more precise and intelligent management. This
stabilizes or increases yields while saving on inputs such as fertilizers, seeds, and
pesticides. It also reduces environmental pollution and makes farms more resilient.
Targeted knowledge transfer is necessary to successfully establish smart farming
in agricultural businesses. Although 73 percent of Austrian farmers say they are
interested in smart farming training, only 34 percent have participated in such
training at least once. Low-threshold training opportunities are needed to close this
gap between interest and actual participation. This requires a multidimensional
approach that includes both face-to-face and online formats, low-cost local
offerings in rural regions, and active promotion. The impact of such training courses
is clearly evident: acceptance of and willingness to invest in smart farming
technologies are increasing significantly. This insight makes it attractive for the
agricultural machinery industry to offer smart farming training courses. Training
courses tailored specifically to the requirements of agricultural businesses can
facilitate effective knowledge transfer. This will enable Austrian agriculture to take
advantage of smart farming technologies and support future-proof development.
Activity 3.3 – Implementation of EU educational approaches (Micro-Credential, RPL, VNFIL, open access)
The project will set out guidance for the design and description of Micro-Credentials to facilitate their transparency and recognition. It will set out standard elements that are complement to EU standards. This activity will focus on quality, transparency, relevance, valid assessment, learning pathways, recognition, portable and learner cantered.
A Handbook for micro-credential development will be finalized within the project, focusing on criteria like relevance, reliability, recognition, and learner-centred approaches, and based on ECTS and EQF. The project partners research the role and relevance of micro-credentials in the agricultural sector and will adjust USAGE modules for competence-oriented short courses (5-15 ECTS) based on the European approach. The handbook details EU recommendations, guidelines, validation procedures, and links to EQF, guiding the design and quality assurance of micro-credentials.
This report presents the outcomes of Activity 3.3, which focuses on the implementation
of European educational approaches within the context of smart-farming education and
training. The activity addresses a core challenge faced by contemporary vocational and
higher education systems: how to translate high-level EU policy frameworks on skills,
lifelong learning, and recognition into concrete, operational solutions that respond to
sector-specific needs while remaining interoperable across countries and institutions.
Activity 3.4 – Networking and applying dissemination strategies
The first step is a collection of the thematically relevant aspects of Smart Farming and IoT. This compendium will be available digitally and linked to corresponding information collections in Europe, North America, and Asia where possible. This will enable dissemination of knowledge out of EU and make a project more global.
A sector analysis for agriculture education was conducted, forming a basis for creating a network of education experts. A second Master’s thesis is focusing on awareness and acceptance of smart farming technologies, challenges like climate change, and criticisms in the USA and EU. A network of universities and extension centres in North America (Midwest USA) has been established.
Select item to view
Activity 3.4 developed a comprehensive and practice-oriented compendium of Smart Farming
technologies and implemented a dissemination strategy to ensure its uptake among educators,
farmers, and agricultural stakeholders. The compendium consolidates essential technologies,
application areas, opportunities, risks, and adoption factors relevant for modern agricultural
production. It was informed by technological reviews, user surveys, and research on digital
knowledge transfer and international adoption patterns. Dissemination activities integrated the
compendium into university courses, vocational training settings, and international academic
networks. Overall, Activity 3.4 provides a solid foundation for teaching and learning materials in
smart farming and strengthens technology-oriented education for smallholder farmers and
students alike.
Select item to view
The agricultural sector is undergoing significant transformation, driven by adopting smart
farming technologies, collectively called Agriculture 4.0. Precision, smart, and digital farm-
ing innovations promise to enhance agriculture productivity, efficiency, and sustainability.
Historically, the European Union (EU) and the United States (USA) have had similar agri-
cultural sector developments and are world-leading regions in agriculture production. This
thesis investigates the awareness, adoption, and perceived benefits and criticism of smart
farming technologies among EU and USA farmers. Through comprehensive surveys con-
ducted across both regions, this study evaluates the extent to which these technologies are
utilized, the challenges faced in their implementation, and the information channels farmers
rely on to learn about new advancements. The analysis reveals key differences and similar-
ities in the adoption rates and perceptions of smart farming between EU and USA farmers,
highlighting the role of regional policies, infrastructure, and educational outreach in shaping
these trends. The findings underscore the critical need for tailored strategies to promote
smart farming adoption, addressing region-specific challenges such as internet connectivity
and access to information. Ultimately, this research contributes to a deeper understanding of
how smart farming can be optimized to meet the diverse needs of farmers across major ag-
ricultural regions.
Smart farming technologies are becoming increasingly important during the digitalization
and modernization of agricultural operations. While many farms are already making good
use of these new achievements, they are still not very widespread among smallholders. This
could be due to structural differences; larger farms often have more specialized experts, bet-
ter financial resources and more direct access to current developments through training, man-
ufacturer contacts or generally better networking within the sector. Current information and
techniques are often delayed in reaching small farms. Therefore, the possibility of bringing
this knowledge to the end user is of central importance, and traditional teaching and learning
methods must be reconsidered to achieve this. A common denominator among small and
large companies is social media, where specialist information can reach all users equally.
Platforms such as WhatsApp, Instagram and Facebook are actively used, with the content of
agriculturally oriented channels being very popular. Many young farmers state that they reg-
ularly receive new information on current topics such as smart farming. Therefore, an online
survey was conducted in this thesis to determine how information on current topics, with a
focus on smart farming, is perceived and received by small scale farms via social media. The
survey also looks at traditional teaching and learning methods in the context of social media.
The survey shows that social media plays a significant role in the context of knowledge
transfer on the topic of smart farming, particularly among younger, digitally savvy users.
However, traditional knowledge transfer remains of great importance. Most respondents see
traditional teaching and learning methods as having a clear advantage over social media and
online approaches. However, according to survey participants, social media can serve as an
additional source or supplement to traditional teaching and learning methods. A large pro-
portion of participants would like to see more contributions from public institutions via so-
cial media – particularly in the form of explanatory videos and compact, technically sound
content. In this way, social media can be developed into an effective, structurally anchored
building block in the agricultural knowledge system.