## 5 Discussion
### Implications for Teacher Education and the Development of \"Selecting dLMs\"  
Regarding the empirical results, we emphasized several findings in the previous section that educational institutions could take into consideration when developing \"selecting dLMs\" in teacher education. Additionally, we now provide further recommendations concerning training needs and the adaptability of the instrument to other subjects, as well as methodological recommendations for developing \"selecting dLMs\". Concerning the training needs for developing \"selecting dLMs\", one requirement is to present dLMs as options in lesson planning in teacher education. If pre-service teachers are unaware of dLMs and their associated opportunities and risks, they might use inferior dLMs or not use dLMs in their future teaching [9]. Similarly, pre-service teachers should examine dLMs as part of their training to determine, for example, whether and why a dLM increases or decreases extraneous cognitive load and what additional scaffolding and support (subpopulations of) learners may need when using dLMs [3]. Furthermore, the application of dLMs in different teaching phases [9; 10] should be examined, along with a comparison of digital and non-digital learning materials [80]. Here, comparing lecture times, scaffolding, and learner motivation in teaching approximations [45] are just some examples of possible learning opportunities. The automatic grading and feedback of dLMs require a different type of diagnostic competence in pre-service teachers. They need to diagnose and develop learning activities based on the automatic grading information from dLMs, while taking into account the automated feedback from dLMs [1]. In addition, an understanding of the TPACK framework in the context of their respective curricula will enable pre-service teachers to identify content areas where dLMs can support them in their future teaching. Pre-service teachers also need to learn how to decide whether they will enact dLMs as teachers themselves or provide learners with the opportunity to use them. Given the small dependency of content knowledge on reasoning, the development of \"selecting dLMs\" may be more suited for a lecture focusing on technological pedagogical knowledge, complemented with the necessary technological content knowledge. Such a recommendation certainly depends on the specifics of an educational institution [33] and the identified deltas regarding the development of \"selecting dLMs\" and other technological advances. Ideally, dLMs and the development of \"selecting dLMs\" would be interwoven in multiple lectures [12; 33]. Equally important in teacher education is adapting instruments to local requirements and other teaching subjects. The presented four-item instrument and scoring system allow for this, as the scoring of content knowledge (items 1-3) is evaluated within the context of the local curriculum and teaching subject. Furthermore, the scoring of reasoning (item 4) regarding \"selecting dLMs\" is structured alongside TCK, TPK, and TPACK. For TPK, it can be directly transferred to other teaching subjects. The TCK coding applies to mathematics learning content and may require adaptations [20; 27; 52; 53; 80]. Also crucial for the longevity of an assessment instrument in teacher education is the ability to adjust an instrument and create variations so it can be reused without requiring retesting. A straightforward modification is to utilize different dLMs. When doing so, one should use dLMs that are complex enough to provide various reasoning [9; 10] (see Appendix A.1). Another option is, instead of inquiring about learner age and special education needs, to provide these and other contextual factors along with a dLM, as well as the items and the requirement to argue for or against selecting a dLM with those confinements. In addition, specifying the need to reason from a pedagogical and/or learning content perspective and requiring a minimum number of reasons are other possible adaptations.