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Abstract

Simulation-based learning is important in social work education. Most common is human-based simulations. In recent years, computer-based simulations have emerged as alternative. A question is if computer-based simulations differ from human-based, are similar abilities, that is, competence, trained when the simulation is computer-based? Purpose: Survey the international experiences of using computer-based simulations in social work education. Method: A five step scoping review. Databases focused on educational issues and social work was searched (Eric, Sociological Abstracts, Web of Science, Scopus). Sixteen publications were included. Results: Five different didactic categories of computer-based simulations were identified. The most common use of computer-based simulations is to practice student's procedural competence, and in lesser extent to enhance students’ meta-competence. Feedback and reflection are central for computer-based simulation, as for human-based simulations. Conclusion: The study shows a didactic field under development and that computer-based simulations provide opportunities to train self-reflection and critical thinking in social work education.

Keywords

simulation social work education computer-based simulation scoping review

Social worker's daily work experiences are often difficult, facing complex problem requiring both theoretical knowledge and practical skills. Social work educators face similar challenge in education of future social workers. Reconciling theory and practice and developing ways to apply theory in practice is therefore a central challenge for social work educators. Field education, where social work students are supervised by experienced social workers and receive feedback from them, has long been considered as the primary method for achieving the integration of theory and professional skills (e.g., Raskin et al., 1991). Larrison and Korr (2013) argue that the signature pedagogy for social work education is that learning experiences takes place both in field education and the classroom. Thus, they argue that field education is a necessary, albeit not solely a sufficient, component in achieving integration of theory and practical skills for social work students.

However, in recent years several studies indicate that students experience discontinuity when moving between classroom-based teaching and field education (Bogo, 2006; Gursansky & Le Sueur, 2012). Bogo (2015) has shown other potential shortcomings with field education; for instance, students not gaining experience from all groups of clients, or only assuming an observer role, rather than the role of an active social worker. Several researchers have also shown that increased workload for professional social workers has resulted in an increasing unwillingness to accept field practicum students, putting field education at risk (Buck et al., 2012; Ligon & Ward, 2005; Phillips et al., 2018).

In light of these challenges, social work educators have increasingly taken an interest in developing experiential teaching methods that emulate social work practice in the classroom. However, such endeavors are not in itself, new. For several decades, social work educators have used different forms of human-based simulation (Allemang et al., 2021; Moss, 2000) to encourage the integration of theory and practice.

Human-Based Simulation vs. Computer-Based Simulations

The most common type of human-based simulation is the peer-to peer role-play where social work students assume the roles of clients and professional social workers with instructional support from teachers (e.g., scaffolding) (Bogo et al., 2014; Chernikova et al., 2020). A more recent type of human-based simulation is role-plays based on so-called standardized clients, that is, simulations in which social work students interact with one or more instructed actors (Mooradian, 2007). In a scoping review, Kourgiantakis et al. (2020) identified 52 studies that examined simulation-based learning with standardized clients. According to Kourgiantakis et al. (2020), human-based simulations with standardized clients refer to two main areas of training student's competence: firstly, competence of a more overall or general character and secondly, training practical skills specific for the profession. The latter is equal to procedural competence, for example, student's ability to build a professional relationship to clients via correct performance of motivational interviews (Bogo et al., 2014). The former concerns holistic competence. Bogo et al. (2014) define holistic competence as two-sided, including procedural as well as meta-competence. Meta-competence involves the training of students’ cognitive abilities, such as self-reflection, critical thinking, or emotional management (Bogo et al., 2014). Kourgiantakis et al. (2020) also emphasize that human-based simulations must be followed by reflection and feedback in an environment that is safe for the students. Feedback from teachers is crucial for learning, according to Kourgiantakis et al. (2020); however, feedback can also be given by supervisors or peers during the simulation itself or after it has ended. Reflection often takes place in smaller groups where students who participated in the simulation are included. Allemang et al. (2021) shows that reflection on completed exercises gives students a deeper learning and understanding.

Following Kourgiantakis et al. (2020) and Bogo et al. (2014), it can be concluded that the purpose of human-based simulations either foremost concerns training of procedural competence (primarily practical skills) or meta-competence (primarily cognitive abilities).

In recent years, an alternative to human-based simulations has emerged, namely computer-based simulations (Baker & Jenney, 2022; Huttar & BrintzenhofeSzoc, 2020). Similar to human-based simulations, the purpose of computer-based simulations in social work education is to replicate practice scenarios and give social work students opportunities to train professional skills. A question of interest is if the use of computer-based simulations differs from human-based, which has a far longer tradition in social work education. Are similar abilities, that is, competence, trained when the simulation is computer-based?

There are various types of computer-based simulations in social work education, but what they have in common is that the simulation refers to some form of interaction between the computer and the student, with the aim of training different types of professional competences. Computer-based simulations, for example, can take place through so-called microworlds. In a microworld, an experience of a real work situation can be simulated (Wastell et al., 2011). Another type of computer-based simulations is virtual reality, which Huttar and BrintzenhofeSzoc (2020) define as:
an artificial environment which is experienced through sensory stimuli (as sights and sounds) provided by a computer and in which one's actions partially determine what happens in the environment; also, the technology used to create or access a virtual reality. (p. 131)

Virtual worlds can include encounters with a computer-animated client but also merely illustrate a physical environment (Taylor & Dando, 2018). Another type of computer simulation can be a meeting with a client face-to-face in the form of an avatar or Chatbots, that is, “computer programs used to conduct auditory or textual conversations” (Winkler & Söllner, 2018, p. 1). In a recent scoping review, Baker and Jenney (2022) distinguish between several different forms of computer-based simulations, where virtual worlds and interacting with virtual humans are the most common. In conclusion, human-based simulations have a much longer tradition as a didactic method in social work education than computer-based simulations, which represent a new and still evolving approach to experiential learning.

The purpose of this study is to survey the international experiences of using computer-based simulations in social work education. Kourgiantakis et al.'s (2020) scoping review of human-based simulations will be used to contrast between the results of the studies of computer-based simulations included in this review. Four research questions are addressed: (1) What types of computer-based simulations have been documented in social work research literature, (2) in which educational contexts are computer-based simulations used, (3) which competencies are trained through computer-based simulations and (4) how are feedback and reflection handled?

Method

In order to survey a relatively new research area, it is important to have a broad approach when it comes to the research design of the included studies. Here, the purpose is not primarily to report results (effect or effectiveness), which is common in systematic reviews. The choice of survey method for the field is thus the scoping review, an approach used to map the literature in an evolving research field, and which is more accepting of diversity in research designs (quantitative, qualitative, or mixed) (Kastner et al., 2012). This review follows Arksey and O’Malley's (2005) five-step approach for scoping reviews: identifying the research question, identifying relevant studies, studying the selection, charting the data, and summarizing and reporting the results.

Study Selection

A clear and defined definition of computer-based simulation is central to the study. The simulation must relate to some sort of interaction between a human and the computer as well as apply to a real-life situation where the student primarily practices procedural or meta-competence (Bogo et al., 2014; Kourgiantakis et al., 2020).

Furthermore, the publication must provide a description of the computer-based simulation, and the simulation must be completed, which means that reviews, commentaries, and discussions are not included. Publications that solely discuss opportunities and challenges with computer simulations in social work education on a theoretical or technical level are not included. Learning carried out solely via distance learning or digital learning platforms is also not included. The publications must concern undergraduates and MSW students in social work. Studies on further training of professionals are not included. In order to capture the pedagogical development in the field in recent years, publications from the year 2000 to 2021 are included. Included publications must be in English and published in scientific journals.

Identifying Relevant Studies

To conduct a structured search, a librarian at Jönköping University was consulted. The database search was conducted during November 2021. A supplementary search was carried out in December 2021. Search words in English, combined in various ways, included: simulation, computer, data, virtual, “social work”, student, “higher education”, universit. In order to capture publications focusing on educational issues, social work, and interaction between humans and computers, the databases called Eric, Sociological Abstracts, Web of Science were chosen. This search was supplemented by a search in the citation database called Scopus regarding the authors who wrote publications included in this overview.

The search resulted in a total of 167 publications (Eric 6, Sociological Abstracts 27, Web of Science 83, and Scopus 51). Results were exported to Rayyan (www.rayyan.ai/), a web-based application for screening articles, and duplicates were identified and removed. Searches and exclusions at different steps follow the main features of preferred reported items for systematic reviews and meta-analyses (PRISMA) (Moher et al., 2009; Page et al., 2021). In total, the title and abstract of 111 publications were independently screened by the review's two authors, with inclusion, exclusion and maybe marking done individually via Rayyan. In case of ambiguities, the method sections of the publications were also checked. In cases where different results were given, the entire publication was read in full text by both authors, and a joint decision was made regarding inclusion or exclusion in relation to the selected criteria.

To complete the search, the reference lists of the included publications were studied, whereby three publications were added to the result. Based on previous knowledge, another publication was added. The latter was not indexed in the selected databases, nor referenced in the reference lists of included publications. See Figure 1 for an overview of the relevant studies.

Figure 1.
Identification of studies.

Quality Review

The 16 included publications were reviewed for quality, according to the knowledge quality framework that Pawson et al. (2003) presented for research studies in the field of social care and social work. The review includes an assessment of the study's: Transparency—are the reasons for it clear? Accuracy—is it honestly based on relevant evidence? Purposivity—is the method used suitable for the aims of the work? Utility—does it provide answers to the questions it set? Propriety—is it legal and ethical? Accessibility—can you understand it? Specificity—does it meet the quality standards already used for this type of knowledge? The 16 included publications met all the criteria for the quality review.

Charting the Data

The research questions have formed the basis for structuring relevant information from the included studies (Peters et al., 2015). The chart comprises the following categories: (1) Year of publication and country; (2) Method, sample, and measure; (3) Competence, both procedural and meta-competence; (4) Categories of simulations, didactic setting, and purpose; and (5) Results. Both researchers discussed the accuracy of the charting.

Results

The 16 selected articles were published between 2005 and 2021, 15 of which during the years 2013–2021. Out of these 15, almost half (7) were published in the last three years. Thus, the number of research studies where computer-based simulations in social work education are treated has increased during the last decade. Similar results are also shown in Kourgiantakis et al.'s (2020) review of human-based simulations, which may indicate that interest in research on alternative teaching methods in higher education of social workers has increased.

The majority of the articles (14) originate in the US; the other two are Swedish and Australian, respectively. The number of participants in the 16 studies varies from 620 to nine participants. In a majority (9) of the studies, the number of participants has been 41 or fewer. Three of the 16 relate to simulation in an interprofessional learning environment where students from the subjects of social work, nursing, or psychology participated jointly. In comparison with traditional human simulation, Kourgiantakis et al. (2020) also report an over-representation of American studies. Regarding simulations for interprofessional learning, however, the percentage is slightly higher, 14 out of 52, than for computer-based simulations.

Different Types of Computer Simulations

Simulations can be constructed in different ways, depending on the purpose of the simulation but also depending on the choice of technical solution or software. Several studies report that commercial software was used (11), but in some cases it seems that a proprietary software has been used (3). In two cases, it is not clear which technical solution was used. The frequent use of commercial software indicates that such software is more readily available to universities today. The limited use of proprietary software also indicates that such development requires extensive financial resources but also specialist competence and time, something that probably not all individual teachers or social work departments possess.

An interesting finding is that there are some clear differences in didactic purpose between human-based simulations and computer-based simulations. Human-based simulations are primarily role-playing, where actors (students or actors) assume the role of clients or social workers to illustrate practical social work (Kourgiantakis et al., 2020). In computer-based simulations, meetings with clients are also practiced, but there can also be completely different purposes for the simulation, for example, interprofessional learning.

In order to illustrate the purpose of the computer-based simulations, the 16 included publications have been classified based on the purpose and construction of the simulation, that is, a didactic categorization has been made. Five different didactic categories of computer-based simulations have been identified (see Table 1). (A) Avatar in virtual reality (4)—here, both the virtual environment and the meeting with a virtual human in the environment form the didactic setup. (B) Student vs. Virtual person (8)—here, the student communicates via the computer with some type of computer-animated person. (C) Student in virtual environment (1)—the didactic approach means that the student is given the opportunity to experience a different social context than his/her own. (D) Student vs. Mannequin (1)—here, the student interacts with a simulation doll as well as role-playing physical actors. (E). Microworlds (2)—here, the student is met by text-based information that will lead him/her on to act in the simulated situation.

Table 1.
Overall Summary of Computer-Based Simulations in Social Work Education.

Author (S), Year, Country Method, Sample, Measure Competencea) Procedureb) Meta Category of Simulation,Didactic Setting,Purpose Results

Casey and Powell (2021). Australia. Mixed, pre- and post-test, N = 42 a) Interviewing skills.
b) Self-awareness. Student vs. virtual client. (eSimulation)
Interview of a child avatar. Students choose questions from lists of four alternatives. Based upon the child's response, four more questions are generated, and the process repeated. A three-hour session.
Purpose: Knowledge acquisition. Provides students with the opportunity to gain specialized skills in a safe and well-structured learning environment.

Egonsdotter et al. (2020). Sweden. Mixed, post-test, N = 176, (N = 24) a) Risk-assessment.
b) Reflective and analytical thinking. Microworld. (Proprietary software)
Two phases. (1) Students were, during a certain time frame, presented with practice-based information in a child protection. A variation in cultural/ethnicity for half of the group: the child's name was of traditional Somali or Swedish origin. The assignment was to decide on the child's need for protection. All information and decisions were computer-based and (2) aggregated data, diagrams, were used for following up.
Purpose: Self- and group reflection on individual assessments and cultural awareness. Students are aware of their different assessments and decisions based on cultural/ ethnicity of the child. Students are aware of expressions of preconceptions.

Hitchcock et al. (2019). USA. Quantitative, pre- and post-test, N = 100 (nurse N = 52 and social worker N = 46) a) Motivational interviewing skills and SBiRT.
b) – Student vs. virtual client. (Kognito)
A conversation simulation using virtual humans (young people) to learn the skills of conversation to promote behavioral change.
Purpose: Help students build their confidence, perceived competence, and readiness to use SBIRT. The student in a social work role feels more prepared for using SBIRT than a nursing student. But the simulation made no differences in attitude towards people with substance use disorder.

Lanzieri et al. (2021). USA. Quantitative, pilot, pre- and post-test. N = 30 a) –
b) Reflective and analytical thinking. Student in virtual world (Wonda VR, mobile device and Google daydream headset)
Through a panoramic urban environment by a pre-recorded voiceover that promotes reflective and analytical thinking as they observe the community through the lens of a social worker.
Purpose: Concrete knowledge of complex urban settings where individuals and communities exist. Learn social work practice concepts, enjoyable, exciting, fun and motivating. Assist student learning about community environments.

Lee (2014). USA. Quantitative, pilot, post-test only non-equivalent group's design.
Group 1 N = 25
Group 2 N = 22 a) –
b) Affective, empathetic, and motivational aspects of learning experience. Avatar in virtual reality (Voki)
Like a role-play but introduces themselves as their avatar, provides some demographic statistics for their role/label (add some intersectionality) in an exercise called virtual cocktail party.
Purpose: Helping students to understand the impact of labeling and stigmatization. Useful and safe medium for integration of cultural competence training.

Levine and Adams (2013). USA. Quantitative, pilot, pre- and post-test. N = 9 a) Case management tasks, active listening skills, helping skills.
b) Reflection over dual perspective, case manager and client. Avatar in virtual reality (Second Life)
Role-play with avatars. Students take on the role of administrator and client at an office.
Purpose: Increase students’ feelings of self-efficacy. Students reported feeling more confident about a range of basic case management tasks, active listening expertise, and foundational helping skills. Through experiencing the dual perspectives of case manager and client, they developed greater empathy.

Nimmagadda and Murphy (2014). USA. Qualitative, post-design. Three nursing students, one nurse practitioner student, and one social work student take part in each scenario. a) Communicate professional judgments.
b) Apply critical thinking. Student vs. Mannequin (SimMan®3G)
The social work student is part of a team of nursing students and meets the simulated mannequin as well as actors who play the role of family members.
Purpose: Bring social work and nursing students together to learn interprofessional skills. Identify as a professional social worker and conduct oneself accordingly; apply social work ethical principles to guide professional practice; apply critical thinking to inform and communicate professional judgments; and respond to contexts that shape practice.

Otters and Hollander (2018). USA. Quantitative, post-test.
N = 34 a) –
b) Critically aware. Microworlds (Family simulation software/agent-based social network simulation)
The student can follow a multigenerational family over time to choose and study how different structural parameters affect the family and individuals.
Purpose: A possibility for the student to understand the dynamics of the family system from three levels, micro/mezzo/macro. The overall survey results suggest that this computerized family simulation can usefully contribute to social work education curriculum. Critically aware of the larger environmental forces impinging on individual family life.

Phillips et al. (2018). USA. Quantitative, longitudinal quasi-experimental with two non-equivalent existing groups of students. Four measurement points
N = 100 VFP (N = 520 traditional students). a) Motivational interviewing, problem-solving therapy, and cognitive behavioral therapy. Identifying and resolving ethical dilemmas.
b) Professionalism, ethics thinking and judgment. Cultural competency and evidence-based practice. Student vs. virtual client. (Not clear)
The student communicates with a simulated client in a virtual environment. Practices listening, problem solving and management. The simulation is part of a whole term.
Purpose: Develop and evaluate the findings of a virtual field practicum. The VFP students fair as well, if not slightly better, than their traditional counterparts when it comes to the development of core competencies.

Putney et al. (2021). USA. Quantitative, pilot, longitudinal, pre- and post-test
N = 19 a) SBI, screening and brief intervention.
b) Critical analysis and self-reflection. Student vs. virtual client (Simmersion)
Student practices SBI (screening and short intervention) with an online patient simulator. An interactive environment in which students conduct face-to-face conversations with fictional characters (young people).
Purpose: teaching and assessing competence in SBI, promote diversity in social work education. The simulation and reflective practice gave students an opportunity to practice their SBI skills and think critically about their own learning.

Reinsmith-Jones et al. (2015). USA Mixed, post-survey and journal writing during the semester. N = 70 a) –
b) Values and knowledge. Feelings attached to discrimination. Learn more about the effects of oppression. Avatar in virtual reality (Second Life)
As an avatar, the student experiences two simulated environments. Holocaust museum and an exercise: Island discrimination exercise.
Purpose: Students are given the opportunity to develop values, skills and knowledge, as well as being a thought-provoking and emotional experience. Group process and decision-making. Emotions, empathetic understanding of events, Critical thinking about the immorality, implications of discrimination. Effects on personal behavior and inferences for the social work profession.

Seabury (2005). USA. Quantitative, Post-test. Compared three groups: Tutorial group, N = 24 Classroom group, N = 19 No-training group, N = 26 a) Skills, suicide prevention and crisis talks.
b) – Student vs. virtual client (Not clear)
Student conducts an interactive interview with a client and receives feedback from a computer. The student's choice affects how the conversation develops.
Purpose: Teaches students how to apply crisis concepts to an individual client in active crisis and how to apply risk factors to a depressed client with suicidal ideation. The computer does not discriminate against users, does not respond differentially to the student's gender and race, and provides each student with a consistent, educational experience.

Smith et al. (2021). USA. Mixed, pre- and post-test. N = 22 a) Psycho-therapeutic clinical training: CBT and MI.
b) Self-efficacy. Student vs. virtual client (Simmersion)
The student communicates with a virtual client, and the student trains MI and CBT
Purpose: A possibility for student to build clinical skills. Students improved their CBT and MI simulation scores and self-reported greater self-efficacy over a 13-week adult interpersonal practice course.

Tandy et al. (2017). USA. Qualitative, pilot, post-test. N = 20 a) Interviewing skills.
b) – Student vs. virtual client (Second Life)
The student interviews a protype of a chatbots, a standardized client that is pre-programmed and runs automatically.
Purpose: A possibility for student to build interviewing skills. Initial results were positive and suggest that the use of simulated clients in virtual worlds as learning objects is worth further development and evaluation.

Washburn et al. (2020). USA. Mixed, post-test. N = 22 a) Diagnostic accuracy.
b) Self-efficacy. Student vs. virtual client (Proprietary software)
The student communicates through text with the patient (which is simulated by a person) to choose the correct diagnosis.
Purpose: Increasing self-efficacy and diagnostic accuracy for common behavioral health concerns. Results support engagement in virtual patient simulation training to increase students’ self-efficacy in brief clinical assessment and support the use of virtual patient simulations to improve diagnostic accuracy.

Wilson et al. (2013). USA. Qualitative, post-test. N = 10 (41) a) –
b) General skills. Understand need for knowledge. Avatar in virtual reality (Second Life)
The actual simulation consisted of two avatars (one client and one social worker) that students would use for interaction within the context of an apartment that was designed to have a number of occupants and environmental hazards.
Purpose: Provide student with the opportunity to practice the engagement and assessment skills associated with the generalist practice model. Simulation helped students to understand the types of skills needed for home visits and to think about the unanticipated situations that can arise in these settings and how they might respond.

It can be stated that in 14 of the 16 studies, computer-based simulation is used to create a didactic situation where the student interacts with a client or experiences a virtual environment. The purpose in these cases is to give the student experiential knowledge or allow them to practice a skill specific for the profession, for example, motivational interviewing.

Interestingly, only two of the studies mention that computer-based simulation is used as a permanent didactic element in regular university education. On the other hand, it is suggested in the majority of studies that computer-based simulations can or should be implemented in regular teaching at higher education institutions. The relationship may indicate that the development and use of computer-based simulations in social work is, de facto, still in its infancy in social work education.

Another difference between computer-based and human-based simulations is whether there is an examination in the exercises or not. For the computer-based simulations, it is only mentioned in one case that there will be an exam for the simulation. The others have training as their primary goal, and not examination. The opposite holds true for human-based simulations. Kourgiantakis et al. (2020) show that the purpose is primarily training (56%) but also that the simulations are, to a relatively high extent, for examination purposes (42%).

Procedural and/or Meta-Competence in Computer-Based Simulations

In just under a third (5) of the studies, the design for the computer-based simulations was that students should act as a professional social worker. For instance, to make a formal decision or give a fictional client advice or recommendation (Egonsdotter et al., 2020; Levine & Adams, 2013; Putney et al., 2021; Washburn et al., 2020; Wilson et al., 2013). For human-based simulations Kourgiantakis et al. (2020) describes that about half of the simulations had such design. The relationship suggests that computer-based simulations can be used for a similar purpose to traditional human simulations. One difference, however, is that computer-based simulation also offers the opportunity to train the student's skills as well as provides some spatial, experiential knowledge, through the student experiencing a real, but simulated, environment or situation.

Procedural-Competence

In most studies, the computer simulation is based on the client being or the situation relating to an adult; however, in four studies, the simulation refers to children/young people (Casey & Powell, 2021; Egonsdotter et al., 2020; Hitchcock et al., 2019; Putney et al., 2021). In 11 studies, it is stated that some specific skill is practiced, and in several, different skills are combined. One of the exercises offered the opportunity to practice investigative conversations with adults or children and thereby provided the opportunity to increase the students’ self-awareness regarding difficulties with professional interviews (Casey & Powell, 2021). In three studies, the simulation had to do with the student practicing to conduct motivational conversations in relation to substance misuse for adults or young people (Hitchcock et al., 2019; Putney et al., 2021; Smith et al., 2021). In another three studies, simulations are described where the aim is to practice skills in other types of client conversations, problem-solving therapy, cognitive behavioral therapy, or to solve ethical dilemmas (Phillips et al., 2018), crisis intervention and suicide prevention (Seabury, 2005) as well as assessment of the client's mental health (Washburn et al., 2020). In the study by Egonsdotter et al. (2020), students are tasked with assessing whether a child is at risk of harm. The student's choices in the simulation are used for reflection on whether the child's ethnicity may have influenced the assessment. Levine and Adams (2013) describe how students are trained to adopt a helping approach in formal proceedings and to practice active listening in relation to the client. A study by Nimmagadda and Murphy (2014) concerns interprofessional training. The specific skill that is trained is for the students to identify their own professional role in teamwork. In comparison with Kourgiantakis et al. (2020), overview of human simulations 36 of the 52 studies focus on students developing specific skills, one of which combines generalist and more specialized skills.

Meta-Competence

In eleven of the overviews of 16 studies, the training of a specific skill is thus described, of which eight studies combine practical skills with meta-competence. In the other five studies, no training of specific skills is reported. The focus of these five simulations was instead to, via a simulated environment or situation, create experiential knowledge that benefits the student's more general competence as a social worker, or rather their meta-competence.

Lanzieri et al. (2021) describe a simulation where the student, via a guided tour in an environment unknown to them, is given the conditions to take a reflective stance based on questions posed in the computer simulation and thereby develop their analytical thinking. Lee (2014) describes another type of simulation, where students participate in a virtual “cocktail party.” With an intersectional approach, the students must meet and assume the role of different people, for example, homeless person with a disability. The aim is, above all, for the students to increase their empathetic ability or their cultural competence. A similar aim is described in Reinsmith-Jones et al. (2015) two simulations. Here, a virtual visit to a Nazi concentration camp from the Second World War is carried out, and a virtual visit to a grocery store, where certain groups are excluded from shopping. The aim is, above all, for the students to develop their empathetic ability and critical thinking. A skill more specific for the profession is carried out by Wilson et al. (2013), where students are prepared for conducting home visits to clients. The aim is for the students to develop increased skills to face unexpected situations. Otters and Hollander (2018) computerized family simulation regarding family system change over time “The simulator evolves family dynamics out of macrocontext, the mezzo social influence network and accumulating microfamily history” (Otters & Hollander, 2018, p. 195).

Feedback and Reflection in Relation to Computer-Based Simulation

In half of the 16 studies, different types of feedback are mentioned as a central aspect of the students’ learning. It can consist of direct feedback during the simulation where the student, via the software, receives feedback about what can be considered the best solution for a given situation (Casey & Powell, 2021). Feedback via the software can also take place on several levels: either through direct signals to the student or in the form of more comprehensive written statements about the student's involvement in the conversation situation (Smith et al., 2021). Feedback can also be provided by a virtual teacher after a conversation exercise (Hitchcock et al., 2019). Another way is for feedback to be given during the simulation, but also directly afterwards by professional social workers (Washburn et al., 2020). Computer-based simulations are also used as part of a larger context, where both peers and teachers support the learning and coach the student who conducts a conversation with a simulated client (Phillips et al., 2018). Similar to traditional human simulations, this also means that students give each other feedback (Levine & Adams, 2013).

Feedback occurs in all but one of the computer-based simulations (Wilson et al., 2013). Wilson et al. state that the students requested feedback and that it was a shortcoming that such was missing. For Nimmagadda and Murphy (2014), where the simulation concerned interprofessional learning, the opposite was true. Here, a thorough debriefing was carried out to take advantage of the students’ thoughts and feelings in order to integrate the experience of the simulation via joint reflection.

In addition to the direct purpose of training a certain skill, computer-based simulations can also have an indirect purpose in the learning situation itself. There, the second aim is for the student, through individual or teacher-led collective reflection, to increase his/her capacity for reflection and analytical thinking (Egonsdotter et al., 2020). Putney et al. (2021) also explain that reflection, in relation to critical thinking, is an indirect purpose of the simulation. Putney et al. believe that because the simulation consists of a practical exercise that is combined with critical reflection, the student develops his/her knowledge, attitudes, and skills.

Lanzieri et al. (2021) show, through their study, how the reflection moment can be integrated in the simulation of the virtual urban environment. In other words, the student receives questions from the program during the journey that should support reflection on how he/she experiences the urban environment. Other didactic techniques for feedback and reflection that are reported are students writing their own diary entries (Reinsmith-Jones et al., 2015) or producing a written report where their own reflection in relation to the computer-based simulation is the focus (Tandy et al., 2017). At the same time, conventional web-based learning platforms are also provided (e.g., WebCT, Blackboard) as a discussion forum for reflection between the students themselves after simulation is completed (Lee, 2014). An approach that differs from other studies regarding feedback and reflection can also be seen in a couple of the included studies. Egonsdotter et al. (2020) state that aggregated data in the form of diagrams is used as a basis for joint reflection on the results of the simulation. Otters and Hollander (2018) state that the computer-based simulation generates data used to produce genograms (a family tree). These are then used for a joint reflective discussion or a classic physical role-play between the students.

Discussion

The purpose of this study was to survey the international experiences of using computer-based simulations in social work education, and contrast the results with an overview of human-based simulations. The review shows that there are primarily two didactic forms of computer-based simulation used in social work education. The first of these variants has as its primary goal to convey practice skills specific for the social work profession, that is, procedural competence, such as motivational interviews. The second variant—which is less common—has as its main purpose to enhance students’ cognitive abilities, self-reflection, or critical thinking, that is, students’ meta-competences. With this latter variant, the ambition is to create a situation where students should be given some type of experience, which then becomes the subject of reflection, individually, in group, or together with social work educators.

However, reflection and feedback are not unique to the latter variety of simulations, but they occur in all but one of the computer-based simulations. In this context, it should be mentioned that Kourgiantakis et al. (2020) make it clear that feedback and reflection are important elements for traditional human-based simulations, so that students are given a better opportunity to develop a holistic competence.

The review also shows that computer-based simulations, in several cases, are used in a similar way to traditional human-based simulations, that is to say that the aim is for the students to practice some form of practical skills where a certain situation from working life is to be imitated as much as possible. In both cases, the students are thus given the opportunity to practice skills in a safe environment without the risk of harming the integrity of real and vulnerable clients. However, there is a clear difference, which is mainly about the fact that via computer-based simulations, there are probably opportunities to create spatial environments that can better imitate professional situations for students in social work.

For the scant third of the studies where the ambition not to train specific skills but only meta-competence, they show that there is a great potential for computer-based simulations to make greater inroads in universities. In these studies, simulations are reported that are not directly linked to skills but rather aim to create environments or situations that are more difficult to imitate, both in a classroom situation or in field education. Primarily, this variant of computer-based simulations creates the opportunity for students to make a personal and group reflection based on a common basis of experience around different situations such as, for example, to visit a concentration camp (Reinsmith-Jones et al., 2015) or conduct a childcare investigation (Egonsdotter et al., 2020).

The variant of computer-based simulations that practice skills has some other advantages. One such advantage could be creating situations where students get to practice skills that would otherwise be practiced in field education. It enables the students to practice, despite the fact that it has become increasingly difficult for social work education to recruit places in the field. That is, by giving students the opportunity to both practice specific skills—and strengthen their cognitive ability by experiencing different phenomena or situations. This means that the students do not have to be completely dependent on their field-based study, but that all students in a class get the opportunity to train the same skills and practice their own competence in social work and thus be better prepared for their future profession. It should also be said that the relatively few studies in this research area indicate that computer-based simulations are still quite unusual didactic elements in social work education. However, the increase in studies in the recent years could indicate a growing interest for alternatives to field studies and classroom-based learning. Another factor that indicates that computer-based simulations are more unusual in social work education is that in several of the included studies, these are described as exploratory or pilot projects (5). In one study, it is stated that it is a prototype that is being tested (1).

However, the results show that some of the problems reported in previous studies for computer-based simulations, to be able to expand in social work education, have probably decreased. In several of the publications before 2015, it is clear that students had a lack of technical knowledge for using computer-based simulations, but also that the technology itself had shortcomings (Lee, 2014; Reinsmith-Jones et al., 2015; Wilson et al., 2013 ). The results here show that these problems have likely decreased in recent years, which warrants an expansive development of computer-based simulations for teachers and students in university education in social work. Possibly, computer-based simulations can also create better conditions for universities to more equally assess, in examination situations, the competence level of students who have trained and met clients in computer-simulated situations. In addition, from a sustainability perspective, this type of location- and time-independent simulations can provide the opportunity for students to participate without complications, for example, long journeys, which can be a win-win, both for the individual student but also for society at large.

The interaction between different professional educations, that is, interprofessional learning, is an even more uncommon goal of computer-based simulations (19%). Similar results have been shown by Kourgiantakis et al. (2020) regarding human simulations (27%). Here, it can be said that there is no major difference between the two forms of simulation in that respect. But as previously demonstrated by, among others, Nimmagadda and Murphy (2014), there can be advantages for education in social work to develop computer-based simulations and didactic systems jointly with other professions.

The use of computer-based simulations in social work education also raises ethical concerns. Dodds et al. (2018) argue that the use of technology, that is, computer-based simulations, could be more theatrical than to have an educational purpose. That is that the use of technology risks trivializing people's social problems or vulnerability. Doods et al. states that computer-based simulations might be more suitable for clinical situations than the complexity of problems the social work profession deals with in real life. However, Meredith et al. (2021) lances a different perspective on technology and ethics. They argue that the use of computer-based simulations provides opportunities for educators to create realistic, interactive environments in which students can experientially learn. Meredith et al. (2021) state that such learning would never be ethical or appropriate in a real-life situation with real clients. They add that “—social work takes place in the context of people's lives, and practice learning must be ethical, never voyeuristic” (p. 6).

In summary, the results reflect a didactic field under development, where the research indicates that computer-based simulations can work well as a complement to field education. In addition, computer-based simulations can provide the opportunity for further training of social workers in terms of developing cognitive abilities and critical thinking. Computer-based simulations also create the possibility of having similar conditions for all students. Students can have shared experiences of situations and meetings, which promote their holistic competence in social work. Furthermore, it can be said that the development of computer-based simulations is part of what Huttar and BrintzenhofeSzoc (2020, p. 139) believe is a way to “stimulate new ways of thinking about social issues,” which also refers to the training of social workers.

Limitations of the Research

A problem in the search for relevant articles has been the use of the term simulation. In relation to the training of social workers, the concept of simulation is multifaceted. There is no exclusive concept for computer-based simulations. This means that the same concept is used to describe different teaching elements. The conceptual confusion creates difficulties in making effective searches in research databases for this type of review. In combination with time and resource constraints, we focused on articles in peer-review journals. Since a criterion for inclusion was that the simulation must be fully completed, that is, performed in a university setting and published, we excluded gray literature. There is a minor risk that results from not yet performed studies are missed.

Another limitation of this study may be that computer simulations were contrasted with an overview of human-based simulations. However, in Kourgiantakis et al.'s (2020) excellent article, different types of role-playing are mostly included, where an actor assumes the role of a client. It limits the field that describes other forms of didactic methods. If computer-based simulations could be compared to studies with more types of didactic approaches, for example, case-based learning, the results of this study can possibly be further clarified. Therefore, this overview does not claim that the comparison takes place in the broad field of all the different didactic methods that exist in social work education, but rather a description of different computer-based simulations in contrast to human-based simulations.

Author (S), Year, Country	Method, Sample, Measure	Competencea) Procedureb) Meta	Category of Simulation,Didactic Setting,Purpose	Results
Casey and Powell (2021). Australia.	Mixed, pre- and post-test, N = 42	a) Interviewing skills. b) Self-awareness.	Student vs. virtual client. (eSimulation) Interview of a child avatar. Students choose questions from lists of four alternatives. Based upon the child's response, four more questions are generated, and the process repeated. A three-hour session. Purpose: Knowledge acquisition.	Provides students with the opportunity to gain specialized skills in a safe and well-structured learning environment.
Egonsdotter et al. (2020). Sweden.	Mixed, post-test, N = 176, (N = 24)	a) Risk-assessment. b) Reflective and analytical thinking.	Microworld. (Proprietary software) Two phases. (1) Students were, during a certain time frame, presented with practice-based information in a child protection. A variation in cultural/ethnicity for half of the group: the child's name was of traditional Somali or Swedish origin. The assignment was to decide on the child's need for protection. All information and decisions were computer-based and (2) aggregated data, diagrams, were used for following up. Purpose: Self- and group reflection on individual assessments and cultural awareness.	Students are aware of their different assessments and decisions based on cultural/ ethnicity of the child. Students are aware of expressions of preconceptions.
Hitchcock et al. (2019). USA.	Quantitative, pre- and post-test, N = 100 (nurse N = 52 and social worker N = 46)	a) Motivational interviewing skills and SBiRT. b) –	Student vs. virtual client. (Kognito) A conversation simulation using virtual humans (young people) to learn the skills of conversation to promote behavioral change. Purpose: Help students build their confidence, perceived competence, and readiness to use SBIRT.	The student in a social work role feels more prepared for using SBIRT than a nursing student. But the simulation made no differences in attitude towards people with substance use disorder.
Lanzieri et al. (2021). USA.	Quantitative, pilot, pre- and post-test. N = 30	a) – b) Reflective and analytical thinking.	Student in virtual world (Wonda VR, mobile device and Google daydream headset) Through a panoramic urban environment by a pre-recorded voiceover that promotes reflective and analytical thinking as they observe the community through the lens of a social worker. Purpose: Concrete knowledge of complex urban settings where individuals and communities exist.	Learn social work practice concepts, enjoyable, exciting, fun and motivating. Assist student learning about community environments.
Lee (2014). USA.	Quantitative, pilot, post-test only non-equivalent group's design. Group 1 N = 25 Group 2 N = 22	a) – b) Affective, empathetic, and motivational aspects of learning experience.	Avatar in virtual reality (Voki) Like a role-play but introduces themselves as their avatar, provides some demographic statistics for their role/label (add some intersectionality) in an exercise called virtual cocktail party. Purpose: Helping students to understand the impact of labeling and stigmatization.	Useful and safe medium for integration of cultural competence training.
Levine and Adams (2013). USA.	Quantitative, pilot, pre- and post-test. N = 9	a) Case management tasks, active listening skills, helping skills. b) Reflection over dual perspective, case manager and client.	Avatar in virtual reality (Second Life) Role-play with avatars. Students take on the role of administrator and client at an office. Purpose: Increase students’ feelings of self-efficacy.	Students reported feeling more confident about a range of basic case management tasks, active listening expertise, and foundational helping skills. Through experiencing the dual perspectives of case manager and client, they developed greater empathy.
Nimmagadda and Murphy (2014). USA.	Qualitative, post-design. Three nursing students, one nurse practitioner student, and one social work student take part in each scenario.	a) Communicate professional judgments. b) Apply critical thinking.	Student vs. Mannequin (SimMan®3G) The social work student is part of a team of nursing students and meets the simulated mannequin as well as actors who play the role of family members. Purpose: Bring social work and nursing students together to learn interprofessional skills.	Identify as a professional social worker and conduct oneself accordingly; apply social work ethical principles to guide professional practice; apply critical thinking to inform and communicate professional judgments; and respond to contexts that shape practice.
Otters and Hollander (2018). USA.	Quantitative, post-test. N = 34	a) – b) Critically aware.	Microworlds (Family simulation software/agent-based social network simulation) The student can follow a multigenerational family over time to choose and study how different structural parameters affect the family and individuals. Purpose: A possibility for the student to understand the dynamics of the family system from three levels, micro/mezzo/macro.	The overall survey results suggest that this computerized family simulation can usefully contribute to social work education curriculum. Critically aware of the larger environmental forces impinging on individual family life.
Phillips et al. (2018). USA.	Quantitative, longitudinal quasi-experimental with two non-equivalent existing groups of students. Four measurement points N = 100 VFP (N = 520 traditional students).	a) Motivational interviewing, problem-solving therapy, and cognitive behavioral therapy. Identifying and resolving ethical dilemmas. b) Professionalism, ethics thinking and judgment. Cultural competency and evidence-based practice.	Student vs. virtual client. (Not clear) The student communicates with a simulated client in a virtual environment. Practices listening, problem solving and management. The simulation is part of a whole term. Purpose: Develop and evaluate the findings of a virtual field practicum.	The VFP students fair as well, if not slightly better, than their traditional counterparts when it comes to the development of core competencies.
Putney et al. (2021). USA.	Quantitative, pilot, longitudinal, pre- and post-test N = 19	a) SBI, screening and brief intervention. b) Critical analysis and self-reflection.	Student vs. virtual client (Simmersion) Student practices SBI (screening and short intervention) with an online patient simulator. An interactive environment in which students conduct face-to-face conversations with fictional characters (young people). Purpose: teaching and assessing competence in SBI, promote diversity in social work education.	The simulation and reflective practice gave students an opportunity to practice their SBI skills and think critically about their own learning.
Reinsmith-Jones et al. (2015). USA	Mixed, post-survey and journal writing during the semester. N = 70	a) – b) Values and knowledge. Feelings attached to discrimination. Learn more about the effects of oppression.	Avatar in virtual reality (Second Life) As an avatar, the student experiences two simulated environments. Holocaust museum and an exercise: Island discrimination exercise. Purpose: Students are given the opportunity to develop values, skills and knowledge, as well as being a thought-provoking and emotional experience. Group process and decision-making.	Emotions, empathetic understanding of events, Critical thinking about the immorality, implications of discrimination. Effects on personal behavior and inferences for the social work profession.
Seabury (2005). USA.	Quantitative, Post-test. Compared three groups: Tutorial group, N = 24 Classroom group, N = 19 No-training group, N = 26	a) Skills, suicide prevention and crisis talks. b) –	Student vs. virtual client (Not clear) Student conducts an interactive interview with a client and receives feedback from a computer. The student's choice affects how the conversation develops. Purpose: Teaches students how to apply crisis concepts to an individual client in active crisis and how to apply risk factors to a depressed client with suicidal ideation.	The computer does not discriminate against users, does not respond differentially to the student's gender and race, and provides each student with a consistent, educational experience.
Smith et al. (2021). USA.	Mixed, pre- and post-test. N = 22	a) Psycho-therapeutic clinical training: CBT and MI. b) Self-efficacy.	Student vs. virtual client (Simmersion) The student communicates with a virtual client, and the student trains MI and CBT Purpose: A possibility for student to build clinical skills.	Students improved their CBT and MI simulation scores and self-reported greater self-efficacy over a 13-week adult interpersonal practice course.
Tandy et al. (2017). USA.	Qualitative, pilot, post-test. N = 20	a) Interviewing skills. b) –	Student vs. virtual client (Second Life) The student interviews a protype of a chatbots, a standardized client that is pre-programmed and runs automatically. Purpose: A possibility for student to build interviewing skills.	Initial results were positive and suggest that the use of simulated clients in virtual worlds as learning objects is worth further development and evaluation.
Washburn et al. (2020). USA.	Mixed, post-test. N = 22	a) Diagnostic accuracy. b) Self-efficacy.	Student vs. virtual client (Proprietary software) The student communicates through text with the patient (which is simulated by a person) to choose the correct diagnosis. Purpose: Increasing self-efficacy and diagnostic accuracy for common behavioral health concerns.	Results support engagement in virtual patient simulation training to increase students’ self-efficacy in brief clinical assessment and support the use of virtual patient simulations to improve diagnostic accuracy.
Wilson et al. (2013). USA.	Qualitative, post-test. N = 10 (41)	a) – b) General skills. Understand need for knowledge.	Avatar in virtual reality (Second Life) The actual simulation consisted of two avatars (one client and one social worker) that students would use for interaction within the context of an apartment that was designed to have a number of occupants and environmental hazards. Purpose: Provide student with the opportunity to practice the engagement and assessment skills associated with the generalist practice model.	Simulation helped students to understand the types of skills needed for home visits and to think about the unanticipated situations that can arise in these settings and how they might respond.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Gunilla Egonsdotter

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Computer-Based Simulations in Social Work Education: A Scoping Review

Abstract

Keywords

Human-Based Simulation vs. Computer-Based Simulations

Method

Study Selection

Identifying Relevant Studies

Quality Review

Charting the Data

Results

Different Types of Computer Simulations

Procedural and/or Meta-Competence in Computer-Based Simulations

Procedural-Competence

Meta-Competence

Feedback and Reflection in Relation to Computer-Based Simulation

Discussion

Limitations of the Research

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iD

References