Clinical training plays a vital role in preparing veterinary students for their professional careers. The primary objective of clinical training is to acquire the essential clinical skills required to deliver optimal care and treatment to animals. The acquisition of clinical skills can be facilitated through a range of learning modalities, spanning from traditional textbooks to mastery learning sessions in the clinic, as well as using both low and high-fidelity simulation models. In veterinary education, students commonly engage with experimental (non-patient) animals to acquire practical experience in various procedures, examinations, and treatments. However, it is crucial to recognize the potential impact on the welfare of these experimental animals (1). Certain procedures or treatments performed during veterinary education may cause discomfort to the animals, and because of this reason can be repeated only a limited number of times, potentially limiting exposure and training possibilities for students. It is important for veterinary education programs to strike a balance between providing students with valuable hands-on experience and ensuring the ethical treatment and welfare of the animals involved (1). This can be achieved through animal-free simulation-based veterinary education (SBVE). Many animal-free simulators have already been developed and organized in, e.g., skills labs (2, 3). Animal-free models are designed to align with ethical standards and the humane treatment of animals. The concept of animal-free models is rooted in the principles of the 3Rs, i.e., replacement, reduction, and refinement. These principles advocate for finding alternatives to animal use, minimizing the number of animals used, and refining procedures to reduce harm to animals (4, 5). This approach is particularly valuable for ensuring that students develop necessary clinical skills before working with live animals.

In addition, animal-free models can offer a level of standardization and reproducibility that may be challenging to achieve with live animals. This consistency enhances the learning process by allowing students to practice and repeat procedures under controlled conditions (6). SBVE aligns with the experiential learning theory (ELT) by providing a structured and deliberate environment for students to actively participate in clinical scenarios (7). Experiential learning theory is a framework that emphasizes the central role of experience in the learning process (8–10). The theory posits that learning is a cyclical and iterative process. The iterative nature of experiential learning in simulation-based education is reflected in the involvement of repeated cycles of simulation training, reflection, and application (8–10). This process allows students to progressively build and refine their clinical skills. Conducting training of clinical skills in a simulation-based environment will allow for mistakes and the repetition of complex procedures without inflicting harm to a living animal. Students can progress at their own speed, ensuring that each individual masters the skill before moving on to other (more complex) scenarios (1, 10–15). SBVE allows for further innovation and quick adaptations to state-of-the-art methods to enhance clinical skills training for the next generation of veterinary professionals.

SBVE has become the subject of increasing investigation and reporting and aiming to setup organized skills labs (2, 3, 12, 16, 17). Notably, the study by Noyes et al. suggests that simulator training within veterinary education can yield positive outcomes for clinical skills development (2). However, the effectiveness of SBVE is evaluated through diverse learning outcomes, including knowledge acquisition, retention, procedural skills acquisition, quality of clinical decision-making, and confidence levels. This variety in criteria complicates the interpretation and comparison of SBVE effectiveness across studies (2). Moreover, while there is existing research exploring the general effectiveness of SBVE and the influence of simulator characteristics (e.g., fidelity) on overall effectiveness, there is limited literature examining how specific simulator characteristics impact individual, separate learning outcomes. This gap in research highlights the need for a comprehensive literature review to elucidate the relationship between simulator characteristics and individual learning outcomes in veterinary clinical skills training. Given the relative lack of exploration in this area, a systematic review is warranted to address this gap and to provide insights into optimizing SBVE for enhanced educational outcomes in veterinary medicine.

A clinical skill is a comprehensive and all-encompassing concept that involves various components open to training and refinement. The clinical skills training consists of a learning process that entails interrelated components, specifically, learning goals, learning activities, and learning outcomes. Learning goals are the specific objectives that define what students are expected to know or achieve and lend themselves to focused training. Learning activities are the practical experiences, simulations, or exercises designed to facilitate the attainment of these goals. Learning outcomes are the results of clinical skill training. Within a specific clinical skills training, one or multiple learning outcomes can be measured and reported, providing a nuanced evaluation of both the acquired (sub) skills through that training and prior initial (sub)skills (18, 19). In the scope of this review the focus is on these separate measurable learning outcomes. Moreover, it is important to recognize that the results of clinical skills training can extend beyond the formal learning objectives, e.g., boosting self-efficacy or social skills. Together, learning goals, learning activities, and learning outcomes create the scaffolds of a learning process for students to develop the practical abilities required in clinical settings (2, 18–20). Investigating how specific simulator characteristics contribute to the learning process of students during simulation-based clinical skills training can provide new insights. In essence, the purpose of this systematic review is to discern which type of learning outcomes are used to evaluate specific learning goals of clinical skills training and to grasp the impact of diverse simulator characteristics on the measured learning outcomes in clinical skills training.

To address the aforementioned aim, the relation between learning outcomes and simulation-based clinical skills training in veterinary education was investigated.

In particular we addressed:

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards of quality (21). This study has been preregistered on Open Science Framework (osf.io/3m6fz).

Following the search strategy 103 papers were included for further data analysis. The studies are listed in Supplementary Document 3. Figure 3 shows the total number of papers in our study, arranged by year of publication. The last decade showed a significant increase in SBVM papers, with 70% of the papers published in the last decade (n = 72 of n = 103 total papers).

The (sub) components of “Learning goals,” “Learning activities,” and “Learning outcomes” per study were succinctly summarized in Table 2.

This study investigated the interplay between “Learning goals,” “Learning activities,” and “Learning outcomes,” highlighting which simulator characteristics were used to create learning activities that align with both the learning goals” and the intended learning outcomes. As the literature indicates, in simulation-based education it is important to provide a structured, constructively aligned process where students experience relevant and effective education (7, 31–33). Through constructive alignment, students are more likely to understand what is expected from them, engage more effectively in activities that directly support their learning, and be assessed more accurately in a manner that reflects the intended learning outcomes (34–37). The result of this study underscores the importance of aligning the learning process in simulation-based clinical skills training.

Within the included studies we have identified a variety of simulator technology in SBVE. This study shows that static and screen-based simulators are most commonly identified. Static simulators were linked to the acquisition of “Procedural steps” and screen-based simulators were mostly linked to both “Relevant knowledge” and “Clinical reasoning” acquisition. Although our results were derived from the included studies, other publications outside the scope of our review have noted some limitations with respect to screen-based and static simulators (2, 38, 39). For example, Liebig et al. demonstrated in their study that screen-based simulators can deliver theoretical concepts effectively (40) but their ability to facilitate practical application may be questionable (15). This is supported by the study of Datta et al. which shows that the translation into real-world clinical skills of knowledge gained through the use of these simulators might not always be seamless (15). The study of Al-Elq described that static simulators are restricted in addressing the dynamic and unpredictable nature of real clinical environments, therefore limiting students in preparing for more complex clinical scenarios (14). In addition, screen-based and static simulators are considered more passive simulators through the lack of physical interaction and tactile feedback, which could hinder the development of crucial skills. These simulators do not actively support learning, and information obtained through active engagement is retained better than information acquired through passive education (15, 41). Thus, these findings highlight the importance of aligning “Simulator technology” with “Learning goals” and “Learning outcomes.”

In addition, other simulator characteristics were examined, such as “Type of simulator” and “Use of simulator.” This study demonstrates that part-task-driven simulators were linked to “Competence” learning outcomes. This is explained in the study of Datta et al. that reported part-task-driven simulators for their targeted skill practice and the ability to isolate and focus on specific aspects of a procedure. These simulators provide students with a safe environment, in which they can make and experience mistakes, to acquire and refine procedural skills before applying them in clinical settings (15). Furthermore, this systematic review reveals that event-driven simulators were primarily linked to learning outcomes regarding “Knowledge.” As reported by the study of Datta et al., event-driven simulators can excel in assessing knowledge-based learning outcomes, as they create contextualized scenarios for practical knowledge application (15).

Our study also investigated interactivity as a simulator characteristic. Most studies included in this review describe interactivity as an essential feature. This is supported by the papers of Musa et al. and Koukourikos et al. who reported that interactive simulators facilitate student engagement and promote active participation, enhancing skill acquisition (28, 42).

Understanding and addressing any misalignments within the learning process certainly helps to improve the overall educational experience and support students in achieving their learning goals (43, 44). These misalignments can occur not only in “Self-evaluated learning outcomes” but also in the instructional design and implementation of simulation-based education. By considering both the development and implementation perspectives, as well as the student’s interaction with the simulator, a more cohesive and effective learning environment is needed. Self-evaluated learning outcomes can give relevant insights into the quality of education in particular related to student’s self-confidence (40, 45). When students engage in self-evaluation, they assess their own learning progress, which can include aspects related to self-efficacy. Encouraging reflection and self-evaluation as part of the learning process can enhance self-efficacy and confidence. When students recognize their progress and acknowledge their accomplishments through reflective cycles, they are more likely to feel competent and motivated to continue learning. This approach corresponds with the principles of the experiential learning cycle, which emphasizes the importance of concrete experience, reflective observation, abstract conceptualization, and active experimentation. Bajpai et al. and Liew et al. described the importance of considering the diversity within a group of students in terms of “Self-evaluated learning outcomes” (44, 45). Students may have varying levels of confidence in their abilities, different goals they wish to achieve, and diverse ways of evaluating their own progress. This can influence how students perceive the quality of SBVE in the context of their own development. On the contrary, misalignment in the SBVE learning process, a disconnect between student expectations and actual educational outcomes, can result in students feeling less confident or satisfied with their learning experiences (40, 44, 45).

An example of where students may feel disengaged and less satisfied, is found in the dimensionality used in the learning process. The prevalence of two-dimensional (2D) simulators, such as screen-based ones, were frequently identified in the included studies but contrasts with the hands-on nature of training, as noted by Datta et al. and Liebig et al. (15, 40). Individual differences in spatial abilities further exacerbate this misalignment, particularly in learning anatomical knowledge. In clinical settings, understanding three-dimensional (3D) spatial relationships is important, yet both 2D and 3D simulators are used for training anatomical knowledge, despite their differing effectiveness (46–48). Moreover, measurement tools, mainly written exams but also, e.g., within-simulator tools to provide users with feedback, remain predominantly 2D. For effective learning, both the “Learning activity” and measurement tool should align with the “Learning goal,” emphasizing the necessity for 3D offerings (49). These findings show that the simulator characteristics play a crucial role in alignment of the learning process. Therefore, a one-size-fits-all approach to simulation-based learning can never apply for all students and stages of the curriculum (50). With its adaptable simulator characteristics, SBVE can provide educational experiences that can be tailored to meet the diverse needs of students. Further research is needed to explore how individual preferences and differences influence simulation-based clinical skills training.

It is of utmost importance to continue innovating educational methodologies and technologies that are proven to be beneficial for students and that can safeguard animal welfare. This underscores the need for educational institutions to embrace such innovations, ensuring that the training provided is both ethical and effective.

The limitations of this paper include those from the inclusion and exclusion criteria, and potential publication bias. Publication bias, a significant concern in systematic reviews, arises when studies with positive results are more likely to be included, while non-significant findings are excluded. Contributing factors include the inclusion of many small studies with positive outcomes, excluding non-English studies, and ignoring “grey literature” like conference proceedings and dissertations. Despite efforts to minimize publication bias, complete avoidance is unrealistic. Though “grey literature” was not automatically excluded, none adhered to the selection criteria.

The risk of bias assessment included the aspects of the risk of bias analysis for each study, according to the Cochrane guidelines. Most studies maintain a low risk of bias rating, demonstrating adherence to rigorous methodologies with respect to randomization, intervention knowledge, measurement consistency, and data analysis. It is important to note that the majority of the studies reported that outcome assessors were aware of the intervention, and it could potentially influence the assessment. However, due to the control measures generally mentioned, the overall bias remains low (Supplementary Figure 1).

A notable limitation of this study lies in the categorization process used to classify the reviewed papers. Although specific criteria were established for categorization, these criteria were developed by the reviewers and applied to the papers according to their assessments. Since the categories used in this framework were not explicitly defined in the original studies, the process involved making judgment calls to assign extracted data to the categories and subcomponents. This reliance on subjective interpretation introduces a potential for bias. The heterogeneity in research methodologies and approaches complicated the synthesis of findings, emphasizing the need for standardized evaluation metrics and methodologies in future studies. This variability highlights the evolving nature of SBVE research and the ongoing efforts to establish frameworks for assessing its impact on veterinary education.

This study’s comprehensive analysis of “Learning goals,” “Learning activities,” and “Learning outcomes” within simulation-based veterinary education provides valuable insights for curriculum development in veterinary clinical skills training. Overall, the insights gained from this study have the potential to refine veterinary education by promoting evidence-based instructional strategies and the strategic integration of simulators. The study not only contributes to refining educational practices but also calls for a deeper consideration of the alignment between learning goals, learning activities, learning outcomes, and measurement tools. By embracing the potential of SBVE, educators can better cater to diverse student needs and foster optimized skill acquisition and application in veterinary clinical practice. By understanding the interconnectedness of learning goals, learning activities, learning outcomes, and measurement tools, educators could better foster skill acquisition and prepare students for real-world clinical scenarios with enhanced competence and self-efficacy.