Digitally native” (Kirschner & De Bruyckere, 2017) and “technically proficient student teachers” (Almås et al., 2021) do not necessarily know how to use those technologies effectively for their own learning, and digital readiness does not per sé result in learning and target-aimed teaching with digital technologies. Due to the emergence of computers in schools, significant research interest has been invested in teachers’ knowledge of technology integration into teaching (Baier & Kunter, 2020; Scherer et al., 2018), cf. TPACK (Koehler et al., 2014; Koehler & Mishra, 2009). Conversely, less attention has been given to the self-regulated learning knowledge (Karlen et al., 2021) that student teachers build, nor the beliefs (Darmawan et al., 2020; Scherer et al., 2018; Vosniadou et al., 2020) that they hold towards digital self-regulated learning (Greene, 2021; Karlen et al., 2021). “Online Self-Regulated Learning”  has been coined to describe the mode of e-learning in structured online learning scenarios, such as MOOCs and Learning Management Systems (LMS) of higher education institutions. However, the technological affordance in distance teaching and learning, as demonstrated by *emergency remote teaching* during the Covid19 pandemic, puts the emphasis on technologies rather than learning. Therefore, this project aims to explore the fundamentals of learning in, with, about, and even despite digital technologies. With “Digital Self-Regulated Learning” (DSRL), I aim to explore the intersection of self-regulated learning (Karlen et al., 2021; Panadero, 2017; Vosniadou et al., 2021) and digital technologies in the teaching profession, which is the domain-general and purposeful use for the teachers’ professional- learning and development. This idea links with Professional Digital Competence (Karlen et al., 2020), defined as a universal set of competences and knowledge that fosters digitality-related learning across all domains in the teaching profession and across the professional lifespan, beyond the integration of technologies into teaching. Additionally, because teachers have communicative obligations in school development processes that are also undergoing digitization, it is important to understand the principal functions of technologies in the context of sustainable school development (e.g., digital device decisions instead of simply tool application). Research on teacher professional development suggests that teachers must be capable of self-regulating their own learning with digital technologies as a prerequisite for fostering SRL skills in their students (Greene, 2021; Karlen et al., 2021; Almås et al., 2021). This is framed from a perspective of a teachers’ professional role and identity (Zimmer et al., 2021). Setting the term “digital” semantically apart from “online/e-learning” - wherein digital technologies function as a medium of transfer (i.e., utility) - opens the aim of the project to define digitality as a condition and digital technologies as learning objects (Knox, 2019; Stalder, 2021). This configurative systematic review (Zawacki-Richter et al., 2020) evaluates and synthesizes the current empirical results on student teachers’ knowledge of self- regulated learning with, and about, digital technologies, as well as their attitudes towards digital self-regulated professional learning (Darmawan et al., 2020; Scherer et al., 2018; Tondeur et al., 2016; Vosniadou et al., 2020) and answers the following two research questions:
1. What is the current empirical evidence on student teachers’ knowledge and attitudes towards digital self-regulated learning?
2. How are knowledge and attitudes measured and operationalized in the context of digital self-regulated learning?

For data retrieval this systematic review has taken the databases _SCOPUS_, _Education Source_ and _Web of Science_ into account. The decision against PsychInfo and Wiley is within the scope of the configurative nature of the review as the combination of self-regulated learning is an umbrella term itself and entails a significant amount of variables and constructs that are measured. Digital self-regulated learning, as elaborated above, puts the omnipresence of digital technologies into perspective as an all-encompassing condition (Knox, 2019). In the current systematic review specific inclusion and exclusion criteria have been put into place for the first phase of data retrieval and narrowing the corpus in an abstract screening. Regarding the database settings the search string targeted the following main concepts ((Student Teachers)), ((self-regulated learning)), ((knowledge)), ((attitudes)) and ((digital technologies)). The construction of the search string underwent 7 major and 11 minor iterations and besides synonyms that play an important role in discourse construction around such semantically rich composita and terms, the proximity operator has been made productive. Additionally, the databases were all set to capture the time frame of ten years between 2012 and 2022. Another pre-requisite taken within the database browser interface, was the publication in the English language as well as the fact that the articles had the criterion of being quality assessed contributions which had undergone peer-review before publication. Therefore, only articles from peer-reviewed academic journals were taken into consideration (Zawacki-Richter et al., 2020). The total corpus that could be derived via this method from the above mentioned databases contained a total number of 4.250 articles (N=4.250). For the abstract screening the software Rayyan was used via the browser interface. The software detected 30 more duplicates that were resolved by deletion of one of the two occurrences per entry. The abstract screening was facilitated by 4 raters and followed the tight agenda inclusion- and exclusion criteria, that were accompanied by interrater-reliability testing (Fleiss Kappa, 0.64, Belur et al. 2021). From 4.250 articles, 169 could be taken into considerations after the abstract screening, loading full-texts facilitated to exclude additional articles, so that the final corpus of this study contains 63, after six titles could not be retrieved as full-texts (cf. PRISMA, Moher et al., 2015) . The qualitative, descriptive and corpus-linguistic data extraction is facilitated with a form in LimeSurvey that follows an if-statement structure which combines descriptive data scales with open-ended qualitative data questions.

First preliminary results suggest that the following list of scales answers research question (2), concerning the scales and instruments to measure digital self-regulated learning attitudes: general attitudes towards technology (GATT), educational attitudes towards technology (EDATT), general ICT efficacy, pedagogical beliefs (student centered / transmissive), Teachers’ Emphasis on Developing Students Digital Information and Communication Skills (TEDDICS), Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), values. The modellation of the digital self-regulated knowledge scales is more complex it contains as well the meta-learning strategy knowledge (cf. SRL knowledge) as also the digital principal knowledge (cf. technological knowledge, TK, Mishra & Koehler, 2009). Additionally, the synthesis of the empirical results answering the first research question suggests, that the complexity of variables measured will derive a puzzle of components to prioritize from, and DSRL as the theoretical compositum I have argued in the rationale above is not represented in the dataset adequately. A lot of the discourse about teachers' technological knowledge and attitudes has been shaped around the theoritical frame of TPACK, which shifts the knowledge and attitudes always into the context of teaching in the classroom.

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