Higher education didactics provides an analytical lens for examining how learning, teaching, and assessment are organised as situated practices that structure participation, responsibility, and subjectivation. Educational processes can thus be described as relational arrangements in which expectations, roles, and trajectories are continuously produced and stabilised. In times of digitalisation and the increasing integration of AI-supported systems, these arrangements are increasingly influenced by infrastructures that anticipate learning processes and prestructure participation.

This presentation analyses how higher education didactics is reconfigured under digitally mediated conditions. Focusing on AI-supported mentoring, feedback, and assessment practices, it examines how predictive and classificatory systems intervene in core didactic dimensions by organising visibility, comparability, and relevance prior to pedagogical interaction. Rather than presuming technological determination, the analysis traces how these systems become embedded in didactic arrangements and interact with situated educational practices.

Drawing on a cumulative research program combining conceptual analysis, systematic literature reviews, and qualitative interpretive studies in higher education, the presentation offers a descriptive account of how didactic responsibility is redistributed within digitally mediated didactic arrangements. Two empirical constellations illustrate how learner subjectivation and participation are configured through these arrangements without being fully determined by them.

Across mentoring, assessment, and feedback practices, AI-supported systems and situated didactic arrangements interact in ways that jointly reorganise how learning trajectories are oriented, interpreted, and navigated. Predictive classifications, procedural standards, and pedagogical practices become entangled, shaping when and how reinterpretation, deviation, and negotiation are possible. Within these configurations, comparability, contextual interpretation, and dialogical engagement are continuously recalibrated rather than clearly separated. Democratic agency appears, in this perspective, as an effect of how participation is dynamically configured within these interacting arrangements. This presentation contributes to current debates on the future of higher education didactics under conditions of digitalisation.

Introduction

Digital competencies are essential for social participation and are integrated in most educational curricula. However, recent research showed that the development of students’ digital competencies depends heavily on family, social, and structural conditions (Fraillon, 2024). This highlights a digital divide among students, which directly affects their access to, use of, and motivation regarding digital media, as well as their digital competencies and consequently, their participation in today’s world (Heinz, 2023). Addressing this disparity requires teachers to have the necessary competencies to counteract the digital divide purposefully (Heinz, 2023). However, many instruments already exist that assess teaching digital competencies (e.g., Lachner et al., 2019), and an initial instrument addresses teachers’ differentiation competencies regarding students’ differing digital competencies (Runge et al., 2023), there is currently no research that examines and assesses teachers’ competencies with a specific focus on factors related to the digital divide (Van Dijk, 2020).

Aim of this study was therefore to first develop an instrument for assessing Teachers’ Competencies in Addressing the Digital Divide (TeCoDD), and second to validate the instrument TeCoDD and to examine teachers’ levels of competence. Accordingly, we asked the following research questions:

- How valid does the developed measurement instrument assess teachers’ competencies in supporting students who are negatively affected by the digital divide?

- What competencies do teachers have to addressing the digital divide purposefully?

Methods

To answer the research questions, we developed a scale to assess teachers’ competencies in supporting students affected by the digital divide in a negative way based on the Digital Divide theory (Van Dijk, 2020) and encompasses four main aspects:

1. Promoting access to digital media

2. Promoting motivation to expand digital competencies

3. Promoting competency-oriented use of digital media

4. Promoting digital competencies

To validate the instrument, we conducted two online studies with teachers from the US and UK. In Study 1 with N = 299 teachers (woman 71%, Age: M = 43 years, SD = 12), we investigated the underlying structure of the data by conducting an exploratory factor analysis (EFA). In Study 2 with N = 280 teachers (woman 70%, Age: M = 42 years, SD =12), we aimed to validate the instrument by testing the factor structure using a confirmatory factor analysis (CFA).

Results

Study 1 confirmed a good item fit across all items (.41 ≥ r ≤ .67), moderate item difficulty (.56 ≥ P ≤.77) and good item variance (0.61 ≥ s² ≤ 1.08). The scale provided high internal consistency (ω = .95). In line with theory, the EFA indicated a four-factor structure and medium to high factor loadings (.50 ≤ λ ≥ .90).

Study 2 also provided a good item fit (.41 ≥ r ≤.68), medium item difficulty (.56 ≥ P ≤.78), good item variance (0.62 ≥ s² ≤ 1.12), and high internal consistency (ω = .95). Subsequent verification using CFA showed acceptable model fit (χ²(246) = 667.46, p < .001, CFI = .91, TLI = .90, RMSEA = .07, SRMR = .05).

Descriptive results of both studies indicated similar results. Teachers mostly agreed that they felt competent in supporting students’ access to digital media (Study 1: M = 4.02, SD = 0.67), while they mostly neither agreed nor disagreed about feeling competent in supporting learners in a learning-oriented use of digital media (Study 1: M = 3.31, SD = 0.81). Results showed a descriptive decreasing trend in self-assessed competencies across the areas of fostering access, learning-oriented motivation, and learning-oriented use, with a slight increase regarding fostering digital competencies.

Significance

For the first time, this study provides a new developed and validated measurement instrument for assessing teachers’ competencies in supporting students affected by the digital divide. The results showed a data structure that is consistent with theory and provides a good overall fit. In addition, the results showed that although teachers provide access to digital devices, they are only able to address learners affected by the digital divide to a limited extent. This provides initial evidence that support for teachers in dealing with the digital divide in the classroom is necessary. Further research is needed to increase teachers' competencies and counteract the digital divide.

Introduction:

Digital Technologies (DT) have become a core component of childhood environments. So, childrens’ social participation and educational opportunities require digital competence from an early age. Therefore, ECEC must both enhance children’s development in digital competence and use DT for learning in other domains. Existing digital competence frameworks such as DigCompEdu (Redecker & Punie, 2017), TPACK-Model (Mishra & Koehler, 2006), the Competence Structure Model (Herzig & Martin 2018), and the Model of Media Pedagogical Competence (Blömeke, 2003) are mostly focused on the individual teacher level (e.g. DigiCompEdu, TPACK). Furthermore, they are rarely empirically validated, and often only consider knowledge while neglecting motivational, volitional, and social aspects. None of these frameworks focus on the ECEC level (Dardanou et al., 2023), and do not take performance and specifically interaction quality into account.

This paper presents the DiCE model, a theory-grounded framework of ECEs‘ digital competencies. It is intended to apply to all pedagogical situations in everyday ECEC practice.

Methods:

The model is based on well-established professionalization and competence frameworks (e.g. Fröhlich-Gildhoff et al., 2014; Blömeke et al., 2015) and technological pedagogical knowledge frameworks such as TPACK (Mishra & Köhler, 2006).

On this basis, the DiCe model outlines three interconnected levels of digital competence: preconditions, situation specific skills, and performance. Furthermore, DT-related facets of knowledge, affective–motivational and self-regulatory skills, and contextual and structural conditions in ECEC are incorporated.

Results: A theory grounded model of digital competence of Early Childhood Educators

Preconditions comprise objective and subjective components. Objective preconditions include digital technology knowledge (which digital technologies are available for use in ECEC), digital-technological-pedagogical knowledge (which digital technologies can be used for learning in ECEC, how, and for what purposes), digital-technological-content knowledge (interaction between technology and content, e.g. programming), and digital-technological-pedagogical-content knowledge (how to make domain-specific content accessible using DT).

Subjective preconditions related to DT comprise ECEs’ pedagogical beliefs about DT, motivational orientations (Anders & Oppermann 2024; Fröhlich-Gildhoff et al. 2014), emotions (Scherer & Moors 2019, with achievement emotions playing an important role in learning and achievement sitations; Pekrun, 2024; Jenßen et al. 2023), and self-regulation (Anders & Oppermann 2024; Baumert & Kunter 2011; Fröhlich-Gildhoff et al. 2014).

Situation specific skills are described as domain-relevant perception and interpretation of pedagogical situations involving DT. There is often used the term of noticing (Bruns et al. 2021; Santagata et al. 2020). Stiewe and Ehm (2025) emphasized that noticing in the context of ECE is predominantly described as the interplay of perception and interpretation or as decision-making, and there is a strong focus on perceiving situations that are relevant to individual children or the whole group, and on interpreting these situations as meaningful in the context of DT. There is still limited theoretical and empirical research on interpretation. It is defined as domain-specific, evidence-based assessments of children's performance when completing tasks or solving problems, focusing on task-relevant aspects rather than all areas of child development (Jacobs et al., 2010). While the findings for mathematics already indicate a need for the development of situation-specific skills in the domain of EC mathematics, it can be assumed that a similar situation applies to the domain of DT.

Performance is interpreted as educators’ observable behavior and concerning ECEC, current research is focusing on interaction quality (Anders & Oppermann 2024; Blömeke et al., 2015; Blömeke 2025; Howard et al. 2020). In the DiCE model, performance is defined as interaction processes that promote children’s skills within the Structure-Process Model – Extension (SP-E), targeting children’s domain-specific learning or global learning. Therefore, performance in DT-related contexts both describes supporting children’s learning with DT or includes interactions that explicitly foster children’s digital competencies (digital or analogue) (Boksjö & Ehrlin, 2025).

Finally, contextual factors (institutional/individual factors) and general conditions (structural features) also influence the digital competencies of ECEs.

Implications and Educational Significance of the research:

The DiCE model constitutes a conceptual contribution to systematically describe and analyze ECEs’ digital competencies, addressing both research and pedagogical practice.

While this paper focuses on competencies to foster childrens’ development, digital competencies are also relevant for collaboration with parents and within the institution. Therefore, a broader perspective will also require an expansion of the DICE model in the future.