Anatomy is often considered as a cornerstone of medical education. Not only for surgical subjects, but anatomical knowledge also has value for anyone who performs invasive procedures on a patient and supports examination of a patient and the finding of a diagnosis (Turney, 2007). It is obvious that clinicians, especially surgeons, need a thorough understanding of anatomy, but there is much debate about the best teaching practice for anatomical knowledge (Estai and Bunt, 2016, Turney, 2007). Anatomy educators are facing major challenges in conveying anatomical knowledge and understanding to medical students (Findlater et al., 2012).

Besides traditional lectures and dissection courses, innovative technologies and teaching methods such as augmented reality or virtual dissection tables are increasingly being used in anatomy (Duarte et al., 2020, Raja et al., 2022, Said Ahmed, 2023). These digital teaching methods are also used successfully in clinical subjects with strong anatomical connections (Kaplan et al., 2023). Even combinations between traditional cadaver dissection and augmented reality have already been carried out (McBain et al., 2023). It has been shown that they lead to increased learning performance and can lead to a better understanding of surgical-radiological diagnostics as well as anatomy itself (Bianchi et al., 2020, Raja et al., 2022, Said Ahmed, 2023).

There is evidence that anatomy learning goes through a process of initial learning, forgetting, restructuring and applying, and that anatomy teaching needs to highlight clinical relevance (Smith and Mathias, 2011). Integrating new knowledge in contextual frameworks of relevance can enable students to become engaged in the subject of anatomy (Smith and Mathias, 2011, Turney, 2007). Several reviews showed that contextualized teaching, experiential learning elements, and teaching facilitation are the three major elements of effective anatomy teaching (Abu Bakar et al., 2022). A multimodal approach in teaching is advocated, as there is no single effective teaching method (Abu Bakar et al., 2022). It has been shown, that compared to traditional teaching methods like lecture-based anatomy education, teaching surface anatomy leads to higher student satisfaction and examination scores when performed in a constructive, collaborative, and self-regulative teaching approach (Bergman et al., 2013, Chawla et al., 2015, Ghorbani et al., 2014, Vasan et al., 2011). In such learning environments students apply their knowledge better and exploit their own creativity and intelligence (Bergman et al., 2013, Singh et al., 2019). It has further been shown that collaborative environments lead to higher examination performance (Chawla et al., 2015, VanLeuven et al., 2022). To understand what is happening in these learning environments, their individual elements will be discussed in the next chapter.

When dealing with the term collaborative learning, one quickly realises that this term is used inconsistently in the literature. Often used synonymously, terms such as learning group, group work, or tutorial learning refer to both learning strategies and teaching formats and sometimes merge seamlessly into one another (Pauli and Reusser, 2000).

Collaborative learning is generally defined as a situation in which two or more people learn together. However, there is too much room for interpretation in this definition, as small groups and larger gatherings can fulfil these requirements. In addition, there are many different ways to learn together: face-to-face, digitally, synchronously, or asynchronously (Dillenbourg, 1999). Some authors distinguish between cooperative and collaborative learning formats. In cooperative learning, the group members are divided up and work is shared on tasks. Each individual in a group works on a different part of the task and the subtasks are put together at the end. This is to be distinguished from peer collaboration, in which tasks are worked on together that could not be solved individually (Damon and Phelps, 1989).

Cooperative or collaborative learning therefore are learning formats in which a group of people works together on tasks. This is expected to take place without the involvement of a teacher (Cohen, 1994). The general goal of cooperative learning is that all individuals in the group gain knowledge (Weinberger et al., 2020). The quality of the interaction is essential and a measure of individual learning success. For this to happen, all group members must be actively involved in solving the task. In this way, differing levels of knowledge between individuals can be taken into account to create a common understanding of the subject matter being dealt with (Offir et al., 2008, Pauli and Reusser, 2000).

The following definition is used for the present work: Collaborative learning is understood neither as a method nor a mechanism, but as a learning situation in which interaction between students is expected, which in turn triggers individual learning mechanisms (Dillenbourg, 1999).

Interactive learning groups are particularly appropriate for intensive learning of the content of academic courses. Through different perspectives of the individual group participants, different approaches to solving a task can be considered (Roschelle, 1992). If students realise that interdisciplinary work will be common in later professional life, collaborative learning in academic studies can lay important foundations for this collaboration and positively influence the necessary competencies. Also due to collaborative learning environments students feel responsible for their own performance as well as team performance, a necessary skill in future professional life (VanLeuven et al., 2022). A learning culture is already being developed during medical studies in which collaboration is accepted and appreciated and professional collegiate exchange is seen as the cornerstone of individual learning (Molwitz et al., 2021, Renkl and Mandl, 1995).

When learning groups establish themselves as a collaborative form of learning, peer tutoring can also occur. This refers to the mutual teaching and learning of content in learning groups. One group member takes on the role of the lecturer, for example because he or she knows the subject better and imparts the relevant learning content to the other group members (Damon and Phelps, 1989). Questions can be asked, explanations can be specified, and existing misunderstandings can be clarified (Nieder et al., 2005, Webb et al., 1995). If a subject is not understood, the person explaining it must reformulate or change the wording. Connections are made, examples are developed, or extended literature is consulted in order to convey the content in a comprehensible way. In this way, a deeper understanding of the content is also created for the person explaining it, and gaps in the person's own knowledge can be discovered and closed (Webb, 1989). Restructuring and breaking down of information are important competencies, which are also required by the National Competency-Based Learning Catalogue for Medicine (NKLM) for graduates of medical studies. Their application is shown, for example, in the explanation of medical facts in an explanatory or counselling interview with a patient as a medical layperson (German Association of Medical Faculties, 2021, Langewitz, 2012).

In addition, the exchange in learning groups also fulfils a preparatory function for the examination situation. A significant correlation has been found between pronounced exam anxiety and poorer exam results (Pintrich and Groot, 1990). Here, conducting exam simulations within the learning group can reduce existing exam anxiety. Due to regular feedback in collaborative learning groups, students can gain confidence as they notice that they were able to pass oral examinations (Laakkonen and Muukkonen, 2019).

It is also known that students who feel they can cope with upcoming tasks make better use of their learning strategies. They show increased motivation to work on challenging tasks and recognise that their own efforts lead to learning success (Ames and Archer, 1988, Smit et al., 2017).

In science, the term learning strategies is neither defined precisely nor consistently, since different terms can be understood synonymously or very differently (Artelt, 2000b, Wild and Schiefele, 1994). Rather, learning strategies are a rough construct that describes cognitive and behavioural learning activities. These can serve to master learning tasks and are consciously used by the learner for this purpose (Mayer, 1988, Weinstein and Mayer, 1986, Wild, 2005).

Through the sequence of different learning techniques, learning strategies can also influence learning success by influencing the motivational and emotional state and contribute to the achievement of learning goals. In this context, a mediating role is attributed to learning strategies (Artelt, 1999, Wild, 2005, Wild and Schiefele, 1993).

Different concepts of learning strategies can be distinguished, which consider motivational and cognitive aspects either separately or in combination, and thus make a generally valid classification of learning strategies impossible (Wild and Schiefele, 1994). For the present work, a distinction is made between cognitive, metacognitive, and resource-based strategies. Within these areas, the different dimensions of learning strategies are summarised.

Cognitive learning strategies refer to processes of immediate information intake, processing, and storage. They include repetition strategies, organisation strategies, elaboration strategies, and critical thinking and testing strategies (Pintrich and Garcia, 1991, Weinstein and Mayer, 1986, Wild, 2005, Wild and Schiefele, 1994). An important component of cognitive learning strategies are organizational strategies, i.e., learning activities that restructure the learning material in a suitable way and in alignment with the learning goal to be achieved. The aim of these learning strategies is to transform learning content into a form that is easier to process (cognitively). The creation of diagrams, charts, or outlines are typical organisational strategies (Wild, 2005). They are deep strategies, as they lead to a deeper understanding of the material (Wild, 2005, Wild and Schiefele, 1994). Deep learning aims at grasping the meaning and significance of the learning material, whereas surface learning is primarily used to memorize facts (Fabry and Giesler, 2012, Marton and Säljö, 2005). The different use of deep learning or surface learning is related to learning success in different ways. It has already been shown that deep strategic learning is closely related to learning success through understanding (Artelt, 1999). Other deep learning strategies are, for example, elaboration strategies, critical thinking, and testing strategies. Repetition, on the other hand, is considered a surface strategy, since the application of this learning strategy only leads to a limited engagement with the learning content and does not foster comprehension-oriented learning (Wild, 2005). However, since many learning strategies affect more than one component of the learning process, a clear assignment of certain learning strategies is only partially possible (Wild and Schiefele, 1993).

Metacognitive learning strategies, on the other hand, refer to the active and conscious (self-) control and (self-) management of one's own learning. A distinction can be made between the sub-strategies of planning learning steps, reviewing learning progress, and regulating learning behaviour (Pintrich and Garcia, 1991, Wild, 2005, Wild and Schiefele, 1994).

Resource-based learning strategies refer to competencies in students' self-management, for example managing their own effort, time management, or using information sources and creating an environment conducive to learning (Wild, 2005, Wild and Schiefele, 1994). Learning in collaborative groups is one of the resource-based learning strategies.

It can be concluded that the effective use of learning strategies requires the coordination of domain-specific knowledge, strategy knowledge, metacognitive control, and motivational beliefs (Pressley et al., 1989). Especially in models of self-regulated learning, learning strategies are considered a central element (Pintrich and Garcia, 1991, Wild and Schiefele, 1994). Thus, depending on the author, either the totality of applicable learning strategies or the use of only metacognitive learning strategies and the control of the emotional-motivational processes for structuring one's own learning activities is described as self-regulation (Garcia and Pintrich, 1996, Pintrich and Garcia, 1991).

Of special importance are the learners’ abilities to focus their attention on the learning tasks to be mastered and the learning goals to be achieved, as well as the avoidance of distraction (Pintrich and Groot, 1990, Pintrich et al., 1991). There is evidence that self-regulated learners are much more active in the process of learning. They use different learning strategies, supervise them independently, and can adjust their learning behaviour when they notice that a change in learning behaviour is necessary to learn successfully (Lavasani et al., 2011). It has also been shown that distinct self-regulatory learning is associated with increased learning success. If learning goals are defined independently and the learning process is evaluated, the motivation to learn increases when learning progress is recognised (Ames and Archer, 1988, Garcia and Pintrich, 1996, Pintrich and Groot, 1990). High intrinsic motivation and/or self-regulation is essential for effective learning. When learning motivation is influenced by self-determined behavioural regulation, high quality learning outcomes can be expected (Deci and Ryan, 1993).

Because of its emphasis on teamwork, mastery of content, and problem solving for clinical application, team-based-learning (TBL) is proposed as a useful teaching-approach for courses during the preclinical years (Vasan et al., 2011). Originally developed in the 1970s for business education, TBL has been adopted for usage in medical education. As a big advantage this student-centered instructional strategy allows one instructor to facilitate a large class, while students work in small groups autonomously (Huitt et al., 2015, Michaelsen et al., 1997, Searle et al., 2003). TBL is based on four main principles: At first, teams have to be formed properly and maintained throughout the course. Second, the students are held accountable for their individual work and contribution to team performance. Third, teachers have to provide frequent and timely feedback (Farland et al., 2013, Huitt et al., 2015, Parmelee et al., 2012). It must be taken into account that independent learning groups gain collaboration and communication skills, whereas disadvantages included lack of direction and feedback from tutors (Whelan et al., 2016). Finally, assignments have to be specially designed to promote team development and active learning (Farland et al., 2013, Huitt et al., 2015, Parmelee et al., 2012). These assignments should contain pre-class self-regulated learning with in-class, team-oriented active learning, and critical thinking and discussion in small groups (Huitt et al., 2015, Vasan et al., 2008).

Due to this design, team members are required to work collaboratively and get the opportunity to learn about working within teams and how to evaluate themselves and their peers through peer evaluation. Due to this teaching approach students experience an active learning process that promotes the learning of factual material as well as higher-level cognitive skills (Nieder et al., 2005). Teaching and experiencing self-regulated learning processes are especially relevant, while qualities for life-long-learning like personal initiative, adoptive skill, and sustaining learning practices are distressingly absent in many students (Zimmerman, 2002).

As individual learning mechanisms are triggered in these interactive TBL settings, they meet the definition of collaborative learning very well. As students are held accountable to their own preparation and contribution to teamwork, the aspects of self-regulation and autonomy are promoted in this teaching format. Having a sense of ownership for the contents, goals, objectives, and planning strategies in the learning process is an important part of a meaningful and lasting educational experience (Vasan et al., 2011). Evaluation of a TBL-teaching format based on peer physical examination in small groups showed that students referred to an improvement in self-directed learning with the opportunity to work at their own pace or repeat tasks and exercises later again (Bergman et al., 2013). Moreover, a significant association with greater acceptance, increased enthusiasm, initiative learning ability, communication ability and team awareness were the results after switching from traditional lectures to TBL-teaching formats (Findlater et al., 2012, Rezende et al., 2020, Yan et al., 2018). Student evaluation showed that TBL students understood the material better and were more engaged in clinical problem solving (Vijayalakshmi et al., 2016). TBL was further perceived as a motivator to be a responsible team-member, reinforced self-directed learning, and fostered an appreciation for peer respect (Vasan et al., 2011).

At the Faculty of Medicine Tuebingen anatomical education starts in the first semester with a 60-hour introductory anatomy lecture. After lectures on the propaedeutics of anatomy, the various organ systems are taught, with both macroscopic and microscopic anatomy being treated. This introductory lecture serves as preparation for the dissection course (winter) or histology course (summer) taking place in the following semesters. In addition to the introductory anatomy lecture, the first semester curriculum consists of lectures in biology, chemistry, and physics. These subjects are each accompanied by the corresponding laboratory practical. Students also have a course in medical terminology.

In contrast to the TBL as a student-centered teaching approach, anatomical education in the first semester at the Faculty of Medicine Tuebingen is teacher-centered and apart from the lecture there are no other anatomy courses in which knowledge or lecture content is repeated or deepened. Unlike in TBL settings, where the teacher initiates collaborative forms of learning, the students in Tuebingen have to take care of forming collaborative learning groups themselves. This, collaborative learning only occurs, when students self-directedly form learning groups. The prerequisite for this is that the students know each other, can make contact, and show common learning behavior. Since a clear framework is usually given by the tasks to master at TBL-teaching, less self-organisation by the students is necessary than in the present lecture-based teaching setting in Tuebingen. The selection of suitable learning strategies, timing, and processing of learning content is up to the students themselves.

As a result of the Covid pandemic and the accompanying laws and regulations, universities had to convert their teaching to digital formats and studying in its original form was significantly restricted (Baden-Württemberg State Ministry for Science, 2020, Ferrel and Ryan, 2020, State Government of Baden-Württemberg, 2021). In the process, many different digital teaching formats emerged at extremely short notice, which led to the establishment of the term "emergency remote teaching" (Hodges et al., 2020, Tolks et al., 2021). A significant transition from in-person lecture delivery to not-in­person lecture occurred during the pandemic (Attardi et al., 2022, Harmon et al., 2021). Many medical schools switched to a combination of virtual and in-person teaching. Much preclinical medical education was conducted solely online (Taylor et al., 2022). This was also the case at the Faculty of Medicine Tuebingen, where the introductory anatomy lecture described in 1.6 was held fully digitally and asynchronously in 2021.

Besides gross anatomy, courses such as neuroanatomy, histology or embryology were influenced by the pandemic as well and online teaching increased (Tschernig et al., 2022). All in all, for the whole anatomical community the transition into online-only teaching posed a notable challenge (Darici et al., 2021). Depending on the digital resources and options of each faculty, the quality of the teaching formats differed significantly, and university teaching posed an unprecedented challenge for medical education (Richter-Kuhlmann, 2020, Tolks et al., 2020). Especially subjects and areas, which already work with many practical parts in teaching at the beginning of the studies, had to change to e-learning models and were thus confronted with problems (Varvara et al., 2021).

Some authors are of the opinion, that anatomy educators were likely more prepared to transition to digital teaching due to the fact that methods as lecture capture and pre­recording, have been well established in the anatomical sciences education so far (Harmon et al., 2021). Some authors state that digital lectures enabled a more focused transfer of knowledge and helped lecturers to focus more on relevant learning content when designing their lectures (Böckers et al., 2021).

Although fully digital teaching offers the possibility of flexible, location-independent teaching and learning, concerns were expressed by lecturers that academic dialogue between lecturers and students suffers under digital teaching (Gottschalk et al., 2021). It is emphasised that direct interaction with students in face-to-face courses is of irreplaceable value, as immediate feedback can be exchanged, whereas this is difficult to achieve in online formats (Ferrel and Ryan, 2020). It could even be shown that the transfer to a digital learning environment can be accompanied by a significant reduction in the physiological arousal of students. This can be associated with passivity during the learning process, which is often linked to lower concentration and reduced engagement in the course work (Gellisch et al., 2023). During the pandemic, the majority of students themselves missed face-to-face education. They stated that they need to meet and learn together. This would help them to improve their skills and to be motivated to learn (Boulos, 2022).

Students also must overcome a variety of challenges in the digital setting. Since there is no spatial and temporal structuring like in face-to-face teaching, students must organise their study time on their own. Contact with fellow students is less frequent and almost exclusively digital (Traus et al., 2020). Digital contact with teachers is sometimes limited. Students complained about the lack of social interaction and clinical skills training (Loda et al., 2020). It has also been shown that students had problems coping with changed study conditions, working out the technical and logistical requirements of the digital teaching formats, and forming learning groups independently (Braun et al., 2020). While first-year students face many challenges to begin with, these were amplified by the Covid pandemic and the shift to all-digital teaching. With the start of medical studies, existing learning strategies have to be adapted within a very short time and students have to find their way in a new learning environment (Fabry and Giesler, 2012). They may have to deviate from learning strategies that worked well in school, as these are not or no longer suitable for university studies. Students are increasingly required to work independently on extensive topics, whereas at school, learning content is more pre-structured and regular verifications on learning objectives occur (Schiefele et al., 2003).

Thus, numerous study results show that the learning environment and also the exchange between fellow students play a significant role in the selection and adaptation of learning strategies (Entwistle, 1998, Entwistle and Ramsden, 1983, Trigwell and Prosser, 1991, Wierstra et al., 2003). Students in the first semester usually focus on building up a professional network relevant to their studies and on building personal relationships (Traus et al., 2020). Under pandemic conditions, the conditions to form this personal relationships and study groups were not given. Social integration and personal interaction were more difficult through the pandemic, as contact with fellow students was mostly only possible digitally (Andresen et al., 2020, Braun et al., 2020). Not to be neglected is the fear of infecting yourself or others. This has contributed to the fact that students preferred to stay at home rather than to take part in face-to-face teaching formats, if any were still offered (Schulte et al., 2022). All this hampers the formation of learning groups or other collaborative teaching and learning formats. It is sometimes feared that the lack of intensive exchange can lead to a loss of education (Ferrel and Ryan, 2020). Therefore, special attention must be paid to this feared loss of education, since according to the graduate profile of the NKLM, students should be enabled to act as communicators and members of a team (German Association of Medical Faculties, 2021).

As stated above, due to the Covid pandemic the conditions for getting to know each other and forming study groups independently were drastically limited for first-semester students. Especially in the transition from school to university, with changing learning conditions and limited opportunities for collaborative learning, the full conversion to digital teaching posed a critical challenge for these students. The present research project addresses two research questions.

RQ1: To what extent does the degree of collaborative learning, self-organisation, and self-assessment-ability of first semester students predict the academic performance in an oral anatomy test?

H1: The degree of collaborative learning, self-organization, and the self-assessment-ability of first semester students predicts the academic performance in an oral anatomy test.

H0: The degree of collaborative learning, self-organisation, and the self-assessment-ability of first semester students does not predict the academic performance in an oral anatomy test.

RQ2: To what extent does collaborative learning and self-organisation predict the self-assessment ability of first semester students?

H1: Collaborative learning and self-organisation predict the self-assessment-ability of first semester students.

H0: Collaborative learning and self-organisation do not predict the self-assessment-ability of first semester students.