3.4 DUAL.AI.TEACHer Learning Objectives

For each of the eighteen competencies identified, a set of specific learning objectives has been defined in order to translate the competency into concrete and practical outcomes. These learning objectives specify the knowledge, skills, and attitudes that teachers are expected to develop to achieve the corresponding competency, providing a more detailed and practical description of what mastering that competency entails in practice.

By breaking down each competency into clearly defined learning objectives at different levels, the DUAL.AI.TEACHer Framework facilitates its practical application in professional development, training design, and self-assessment, offering educators a concrete blueprint for progressively building and demonstrating their AI-related competencies

DUAL.AI	Professional Engagement	Digital Ressources	Teaching & Learning	Assessment	Empowering Learners	Facilitating Learners' (AI) Digital Competence
Human-centered mindset	HCM-PE-1a Teachers can recognise common AI use cases in professional communication and networking and the situations where human judgement, presence, or relationship-building must take precedence. HCM-PE-1b Teachers can recognise their own AI-related learning needs and tools that support their continuous professional development. HCM-PE-1c Teachers can summarise how AI is used in their institution for stakeholder engagement and organisational development, including the opportunities and risks it creates for human agency, inclusivity, and educational values.	LO1 LO1 Teachers can ensure human oversight and learner agency in AI-supported processes for selecting, creating, and evaluating digital resources.	Teachers can keep learner agency, human relationships, and teacher judgment at the centre of AI-supported teaching and learning.	Teachers can ensure human accountability and fairness in AI-assisted assessment processes	Teachers can use AI to address diverse learning needs and styles, placing human dignity, equity, and the right to education at the core of every inclusive practice	Teachers can model and cultivate human-centred attitudes towards AI as part of students' reflective digital (AI) competence development
Ethics of AI	Teachers can apply ethical principles and regulatory awareness to their own use of AI in professional practice and institutional contexts	Teachers can identify & mitigate ethical risks in AI-generated or AI-enhanced learning resources.	Teachers can integrate ethical reasoning into decisions on whether on how to use AI for teaching strategies & learning activities	Teachers can ensure that AI-assisted assessment practices meet standards of fairness, transparency, and legal compliance, allowing them to reflect on feedback & improve their assessment practices	Teachers can address the ethical dimensions of AI personalisation, including risks of inequity, data misuse, and exclusion	Teachers can educate students in responsible, critical, and ethically informed use of AI technologies
AI foundations and applications	Teachers can apply foundational AI knowledge to inform professional decisions, engage critically with AI tools, lead AI-related professional learning in institutional contexts	Teachers can critically select & use AI tools for creating, adapting & enhancing digital educational resources based on technical understanding of AI systems	Teachers can apply understanding of how AI systems work to make informed, critical decisions about AI integration in teaching and learning, improving their own teaching practices and instructional design approaches	Teachers can apply AI knowledge to design, implement and evaluate efficient and equitable AI-enhanced assessment practices, and systematically improve their assessment practices	Teachers can select pedagogical strategies and AI tools that support personalisation and inclusion, based on informed understanding of how they function	Teachers can build students' understanding of AI technologies and their societal implications as part of AI competence development