Overall Evaluation and Methodological Considerations of the Study

The present study enhances our understanding of simulation-based education from healthcare facilitators’ and students’ perspectives. It has produced a peda-gogical model that can be used to foster students’ meaningful learning in SBLEs.

The pedagogical model that I have introduced here is the result of previous stud-ies and the two case studstud-ies and DBR cycle. However, it was not truly designed together with practitioners or put into practice in the simulation settings, so there are clearly shortcomings in our application of the DBR approach. In all cases we as researchers were hoping to follow the DBR approach, but the schedules of the

facilitators and students were so tight that we had to give up the co-designing sessions and implementation of the model in practice. Consequently, the collec-tion of data can be best described as case studies, both of which have yielded refinements in the model. As noted, in this study I have developed the pedagogi-cal model iteratively, as suggested by the DBR approach (see also Keskitalo et al., 2010; Keskitalo & Ruokamo, 2011), whereas the Sub-studies have produced use-ful knowledge for the development of the model (cf. Laru, 2012; Muukkonen-van der Meer, 2011). Testing of the model adequately during the teaching experiments would have required the facilitators to modify courses that were part of the estab-lished curriculums, so it would have required too much extra work on their part.

Thus, we decided to evaluate the courses based on our model and gave suggestions for further development of the model and practice. However, in both case studies, almost all of the facilitators were familiar with the model since it was presented to them before the courses, but it should be borne in mind that practical testing of the pedagogical model is still incomplete and further research is needed.

Although the overall design process lacked a joint designing event, multiple viewpoints were taken into account as the research progressed. This is clearly one strength of this study. Following the second case study, the model was discussed and critically reflected on together with three simulation educators, two educa-tional scientists and a service designer. In this discussion we were able to vali-date the model and refine it even further. Furthermore, there seems to be some controversy about simulation-based healthcare education, and the research proj-ect has given me an opportunity to collaborate with enthusiastic facilitators who welcomed us to observe and study their daily practices. I can firmly state that the pedagogical model takes into account the views of the facilitators and students with whom we worked and to whom we listened closely during this study. How these views can be put into practice and how well they work remains to be seen.

The present study took advantage of various types of triangulation: theoreti-cal, methodologitheoreti-cal, data and researcher (Denzin, 1978). This is one of the study’s strongest features. The selection of theories and methods was based on the various aims of the studies, as well as on how to improve the overall validity of the study (Denzin, 1978; Gray, 2004; Säljö, 2009). Most of the sub-studies were qualitative, although through the use of questionnaires I was able to reach quite a large num-ber of students when enquiring about their expectations concerning learning in SBLEs (Sub-study II). A large number of studies in the field of simulation-based healthcare education are quantitative, aiming to measure how much participants have learned, but I think we also need qualitative research to capture the view-points of participants in order to form a complete picture of the phenomenon (Cohen et al., 2011; Cook et al., 2011). Collins et al. (2004) remark that the suc-cess or failure of any given innovation cannot be evaluated in terms of how much

the participants have learned; instead we must use multiple measures in order to see if the innovation in question really works.

In using DBR and case study approaches, methodological triangulation and the inclusion of many participants in this study have yielded quite a large volume of data. During the case studies I collected various kinds of qualitative data (inter-views, group inter(inter-views, video recordings, field notes, learning diaries, open-answer questionnaires) which have helped me understand the present phenomenon com-prehensively. However, some of these methods can be considered as self-reporting, which although commonly used in educational research, may not always be the best choice (Kember, 1997). With these methods there is a danger of misinter-pretation, especially when interviewing subjects in a language in which one is not totally fluent. Our presence in the courses could also have influenced the partici-pants’ performance and, therefore, should be kept in mind.

As I mentioned, some of the data remain unanalyzed, which is typical for the DBR method (Wang & Hannafin, 2005). It has been my choice to leave some of the data unanalyzed and pick the most appropriate data for each study. As Gray (2004) states, the data collection and analysis should be focused in some way, es-pecially when a case study approach is applied. In this study, it was mainly the theoretical framework and research questions that guided me to choose the data used in answering particular questions. However, it should be kept in mind that with different choices the results might have looked slightly different.

In analyzing the data, I have utilized both quantitative and qualitative methods.

In sub-study II, the data were analyzed using quantitative methods (factor analysis and reliability analysis). The Cronbach’s alpha for the study’s subscales was accept-able in each case, which indicated that these variaccept-ables could be used to describe students’ expectations (Nunnally, 1978). Although the gender distribution was un-even, it was a normal distribution for healthcare education in Finland (Saarenmaa et al., 2010). Because of this, I did not attempt to figure out differences in expecta-tions between the genders.

The present study’s qualitative data have been analyzed using a qualitative con-tent analysis method (e.g., Graneheim & Lundman). By enhancing the reliability of the studies I have tried to describe the data collection and process of analysis in detail. The presence of another researcher in the collection and analysis of the data (Sub-studies III-IV) has also helped me strengthen the overall validity of the study (Denzin, 1978), since we were able to discuss and come to conclusions together. Moreover, the video recordings and field notes were helpful in verify-ing the analyses made on the basis of the textual data (Sub-studies IV). Durverify-ing Sub-study I, the participants also had a chance to comment on my interpretations, which enhances the reliability of the results.

One limitation of this study is that there is some variation in terminology be-tween the different sub-studies (Sub-studies I-IV). This can be explained by the quite long research period involved (2007–2015) and because my own learning has progressed during this time. Moreover, there is some disagreement about how different types of simulation technologies should be labeled (Alinier, 2007), and this has sometimes caused some confusion within my own thoughts. For example, from 2008–2009 when the data were collected in the ENVI virtual center, ENVI was a new kind of environment (see Chapter 6), so defining it clearly so that ev-erybody would understand it in the same way was difficult. Towards the end of the study and my learning process, I have started to view it simply as a simulation center (the official name is ENVI Virtual Centre of Wellness Campus™) that houses many different kinds of simulation technologies, including a 3D incident environment with special effects, which is a feature that makes it unique compared to other simulation-based learning environments.

The present study was conducted during different research projects and involved various partners. On one hand, this has been a strength, because the projects of-fered valuable opportunities for the researchers, but it has also been a weakness, since the research partners were selected beforehand. So my position has been that of a project researcher whose work has been framed to some extent by the univer-sity, the project partners and the financiers.

Despite the limitations of the present study, it has broadened our understand-ing of simulation-based learnunderstand-ing and, most importantly, produced a pedagogical model to help practitioners. As a researcher, I have been able to objectively observe the practice and make interpretations based on my educational background while being attentive to the viewpoints of the participants. The evaluation of this dis-sertation is not the only occasion when this study has been examined and assessed.

The sub-studies have been evaluated many times and constructive feedback has been provided by anonymous reviewers of the journals to which I have submitted the articles, and by teachers and supervisors of the doctoral school² with which I have been involved, conference committees and participants, other PhD students, as well as other researchers from my research community. All of these people and their contributions have influenced the overall quality of the study.

2. Doctoral Programme for Multidisciplinary Research on Learning Environments