Teacher professionalism in digital era: Transforming classrooms through purposeful digital training

Professional digital competence, as the editorial defines, includes both foundational and pedagogically specialized knowledge, attitudes, and skills required for teaching with and about technology. The authors distinguish between “basic” and “professional” digital competencies: the former includes skills such as digital communication, content creation, and cybersecurity awareness, while the latter extends to didactic applications of technology in real classroom settings with awareness of learning outcomes and student engagement.

A new editorial published in Education Sciences by Charlott Rubach and Rebecca Lazarides sheds light on a forward-looking agenda for empowering teacher professionalization through digital competencies. The editorial, titled “Empowering Teacher Professionalization with Digital Competencies,” is published the journal (Education Sciences, Vol. 15, Issue 7). 

Based on a series of empirical studies across Europe, the Special Issue synthesizes key strategies and models, particularly the MAIN-TEACH and SQD frameworks, that inform the development of digital competence among both pre-service and in-service teachers.

The publication highlights how current policy demands and technological innovations have converged to make digital fluency not only desirable but essential for today’s educators. While teacher training institutions have increasingly embedded digital learning into curricula, the research identifies major variations in effectiveness, prompting the need for more structured, evidence-based approaches to teacher development in the digital age.

What defines professional digital competence in teaching?

Professional digital competence, as the editorial defines, includes both foundational and pedagogically specialized knowledge, attitudes, and skills required for teaching with and about technology. The authors distinguish between “basic” and “professional” digital competencies: the former includes skills such as digital communication, content creation, and cybersecurity awareness, while the latter extends to didactic applications of technology in real classroom settings with awareness of learning outcomes and student engagement.

The authors argue that these competencies must be cultivated through a developmental trajectory spanning initial teacher education, early-career induction, and lifelong professional learning. This longitudinal process requires explicit attention to the quality of instructional design. The MAIN-TEACH model is introduced as a conceptual framework that identifies three tiers of instructional quality: foundational differentiation, stand-alone components such as classroom management, and content-specific strategies like cognitive activation and formative assessment. When applied effectively, this model allows educators to design training programs that align teaching processes with learning outcomes.

Complementing MAIN-TEACH, the SQD (Synthesis of Qualitative Evidence for Digital Competence Development) model offers six instructional strategies shown to be effective: authentic environments, instructional design, collaboration, reflection, feedback, and role modeling. These frameworks together provide a comprehensive view of how digital competence can be purposefully built.

How can instructional design support pre-service and in-service teachers?

The editorial explores several studies presented in the Special Issue that test specific instructional approaches in teacher education programs. Runge, Hebibi, and Lazarides show that embedding AI-related coursework in university curricula strengthens pre-service teachers’ confidence in using digital tools and their intention to adopt AI in classrooms. Another study by Roeben and colleagues evaluates a simulation-based learning environment that trains teachers to diagnose students’ cognitive engagement in digital settings. The tool helped participants recognize their own diagnostic limitations, supporting the view that simulations can serve as safe yet realistic practice grounds.

Hirsch and Rubach’s longitudinal study demonstrates that isolated strategies are less effective than coordinated instructional designs. Pre-service teachers who experienced harmonized learning activities, such as interacting with digital role models and receiving personalized feedback, showed stronger development of professional digital beliefs over time. Similarly, Aumann et al. explored the impact of internships structured around the SQD model. Pre-service biology teachers who co-designed lesson plans and used video-based instruction in real classrooms reported higher self-efficacy and motivation for future tech integration.

On the in-service front, Amdam and colleagues emphasize that teachers with greater digital competence focus on instructional strategies and student engagement rather than merely access to digital resources. In-service professional development programs, like those assessed by Annemann et al., showed positive effects on attitudes toward technology and its classroom implementation when training included content such as student learning tools and subject-specific applications. A separate study by Fütterer, Wurst, and Goeze revealed that while in-service teachers appreciated interactive and feedback-rich online courses, measurable gains in practical digital skills were less conclusive, pointing to the need for more hands-on practice opportunities.

What are the practical implications for teacher education and policy?

The Special Issue culminates in a synthesis of instructional quality principles that can inform teacher education and policy design. First, the editorial emphasizes aligning teacher training curricula with real-world professional needs. This includes integrating current technologies like AI and emphasizing legal, ethical, and didactic aspects of ICT use.

Second, authentic learning environments, whether through internships or simulations, are crucial for meaningful engagement. Teachers need not just theoretical understanding but the opportunity to apply, reflect, and revise their practice. This cycle, from theory to enactment to reflection, echoes established learning models such as McDonald et al.’s pedagogical sequence and is reinforced by multiple contributions in the volume.

Third, feedback and reflection are highlighted as powerful tools for sustaining competence development. Studies in the issue show that learners who received structured, formative feedback, not only at the end but throughout the learning process, were more likely to internalize digital teaching practices. Role models, especially peer mentors and experienced colleagues, were identified as pivotal to supporting this reflective growth.

Lastly, collaboration emerges as an indispensable pillar. Whether in pre-service settings through communities of practice or in in-service environments via professional learning communities, joint exploration and peer feedback contribute to deeper engagement and knowledge retention. Though the MAIN-TEACH model does not explicitly include collaboration, the research in this issue makes a compelling case for its inclusion in future iterations.

A blueprint for future research and implementation

The editorial also identifies gaps that warrant further exploration. For example, while motivational beliefs such as confidence and perceived usefulness have been well-documented, there remains limited empirical evidence on how to systematically foster practical digital teaching skills, particularly among in-service educators. Moreover, while content differentiation is often discussed, it has not yet been sufficiently analyzed empirically.

Future research should explicitly connect the generic components of teaching quality, like classroom management and socio-emotional support, with digital competence training. The authors call for more transdisciplinary approaches that integrate theoretical models across the domains of teacher training, instructional science, and digital pedagogy.