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C2C Digital Magazine (Fall 2020 / Winter 2021)

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Book review: Computer simulations to improve learner knowledge, skills, planning, and foresight

By Shalin Hai-Jew, Kansas State University 


 


Teaching, Learning, and Leading with Computer Simulations 
Yufeng Qian
IGI Global
2020   336 pp.  


Teaching and learning in the classroom so often involves some level of make-believe and as-if and pretend.  An extension of this applies to the uses of computer simulations, where such extensions of the imagination are extended into vicarious experiences:  clinical treatments, social interactions, geopolitical role plays, language learning games, and business process simulations, among others.  

Simulations are always a limited mimicry of reality, with selected details.  Computer simulations were used for education starting in the mid-1940s with the Monte Carlo method used to “generate all possible outcomes to an event” (Rubinstein & Kroese, 2007, as cited in Qian, 2020, p. xv).  In the current age, computer simulations are used in “medical and healthcare training, business education, language learning, special education, and political science” (Qian, 2020, p. xvi).  This collection Teaching, Learning, and Leading with Computer Simulations, edited by Yufeng Qian, provides some snapshots into the current state of the art, with a mix of works focused on computer-based simulations of various types and applications, and in various stages of design, development, and implementation.  

Harnessing Simulations to Improve Healthcare Training in England 



 
Figure 1:  Healthcare (from Max Pixel) 


Richard Price and Sukie Shinn’s “A Strategic Overview and Vision of Simulation-Based Education in Healthcare in England:  Enhancing Patient Safety and Learner Development” (Ch. 1) describes an ambitious national-level effort to harness simulation-based education to improve training for their healthcare workforce.  The National Health Service (NHS) of the UK was started in 1948, and it currently has 1.5 million employees.  The organization is animated by the premise that “good healthcare should be available to all, regardless of wealth, and services should be provided for free at the point of delivery for all UK residents (NHS, 2016, as cited in Price & Shinn, 2020, p. 2).  [Side quibble:  The hierarchy of the organization (the diagram should be more legible and with sufficient contrast—not white lettering on light gray) (Price & Shinn, 2020, p. 3).]   Simulation (and simulation-based education or “SBE”) is generally defined as “a technique—not a technology—to replace or amplify real experiences with guided experiences that evoke or replicate substantial aspects of the real world in a fully interactive manner” (Gaba, 2004, p. i2, as cited in Price & Shinn, 2020, p. 6)   

Some common simulation modalities in the National Health Service including teamwork (with focuses on communications and safety and coordination), in-situ simulation (such as to enable “multi-professional teams to practice a simulated scenario that reflects how it would be carried out”) (p. 7), “cadaveric dissection and wet tissue simulation” (the first with human cadavers, the latter with animals) (p. 8), simulation “manikins” (both adults and children), and others.  This work describes basic augmented reality, virtual reality, mixed reality, and haptic simulators as possibilities to integrate in the healthcare space.  They take the approach that simulation is one of a number of available options.  

Of course, simulation is only one solution to ensure high-quality learning takes place while reducing the risk of harm and there are numerous other modalities of learning in use such as e-learning and classroom training, which are equally impactful.  Differentiating the impact of simulation and measuring the return on investment of simulation versus other educational interventions is difficult given the volume of training being provided by the NHS (Price & Shinn, 2020, p. 16).    

Early on, five guiding principles were set to align the simulation-based training with outcomes (“safe, effective care”), governance and leadership, resource allocation, multi-professional faculty development, and quality assurance for the education and training (Price & Shinn, 2020, pp. 18-19). Key Performance Indicators (KPIs) were defined to assess performance, such as “evidence that lines of accountability, reporting mechanisms and escalation processes in the delivery of uni-professional and multi-professional SBE are in place, or that plans are in place if not” and “Evidence of or plans in place for faculty to have access to a community of practice / network to promote collaboration and sharing of best practice” (p. 20).  During the work, various challenges were identified and addressed.  Collaborators identified the importance of developing toolkits to support the five guiding principles (including videos), and they identified the need for a community of practice, to support the work.  They defined the need for an effective faculty of trainers to onboard others to sound simulation-based education practices. The coauthors describe “an active network of regional simulation groups across England, facilitated by HEE, in support of the SBE framework adoption” (p. 23) and other broad-scale and distributed support bureaucracies.  Much of this chapter describes planning work, but it is not clear how much progress was made on those plans per se.  The authors note that various healthcare professional organizations and regulating agencies have to adopt this SBE framework, and “HEE local offices, NHS Trusts and other regional organizations” have to align their strategies with this national framework for it to have powerful effect (p. 24).  They describe follow-on steps to build collaborative networks of professionals to actualize this and to ensure quality development and deployment along the way.  This work describes an ambitious project that involves complex expertise and knowledge of public health and other bureaucratic structures in England.  If the various entities and staff can actualize this framework, they should be able to practically train more people with fewer resources to high standards for enhancing healthcare.  


Radiographic Science Education

Christopher Ira Wertz, Jessyca Wagner, Trevor Mark Ward, and Wendy Mickelsen’s “Using Simulation in Radiographic Science Education” (Ch. 2) is based on the idea that medical imaging modalities can benefit from virtual simulation to help learners develop both the science knowledge and the requisite psychomotor skills, to apply in clinical settings. The coauthors cite research about how simulations are integrated in Radiographic Science education:  

Real-life simulation, a common practice in radiographic education, is the use of high-fidelity mannequins, disarticulated phantoms, and real-life people for the practice of radiographic positioning…Virtual simulation, technology-enhanced simulation performed through the medium of a computer software program, offers the added benefits of self-paced learning, repetition, constant access, and instant feedback… (Wertz, Wagner, Ward, & Mickelsen, 2020, p. 38) 

Radiographic technologists “are required to learn and demonstrate the proper patient positions and radiation exposure factors for 37 mandatory exams and 34 elective exams in a clinical setting” with each exam including two to six images in “differing patient positions,” and students have to take a national exam for certification (p. 39).  There are other required clinical competencies:  “patient identity verification; examination order verification; patient assessment; room preparation; patient management; equipment operation; technique selection; patient positioning; radiation safety; imaging processing; and image evaluation” (p. 40).  




Figure 2:  Hand X-Ray (by NFejza on May 23, 2012) 


In this discipline, simulations focus on various body parts for detailed study, such as “head, neck, and torso mannequins for teaching venipuncture and line placement, and ultrasound simulators to hone scanning abilities or practice needle guided biopsies” (Wertz, Wagner, Ward, & Mickelsen, 2020, p. 45).  Mannequins may be “generally mechanical, virtual, and computer-enhanced” (p. 45).  The fidelity of each experience may be low, medium, or high, as compared to the real world.  Simulators enable practice in various procedures and image analyses, among others.  After a light review of the academic studies on clinical training for RS students, the authors provide some suggestions for selecting appropriate virtual simulation technologies (from a limited available set), based on factors like ease of integration into an established curriculum, reliability, and uses in social constructivist learning contexts.  

Orthodontics and Mobile Augmented Reality


As yet, mobile augmented reality (MAR) is a fairly new technology in the pedagogical space.  It enables ubiquitous learning, without locational limitations.  However, it is so new as to be “bleeding edge” as least in terms of the educational research.  Gururajaprasad Kaggal Lakshmana Rao, Yulita Hanum P. Iskandar, and Norehan Mokhtar’s “Enabling Training in Orthodontics through Mobile Augmented Reality:  A Novel Perspective” (Ch. 3) explores the use of such an MAR platform for  “visualization, deliberate practice, effective feedback, and a personalized learning environment” (p. 68).   The coauthors summarize various approaches to orthodontics education in the UK. Then, they review the literature and emphasize the importance of visual learning in this field and the challenges of learning in crowded in-person settings.  They write:  

The complex biological interactions among teeth movement, force application and force generation for tooth movement, force distribution, and torque are a few examples for which the student must rely on his/her imaginative skills to grasp the concept. For teeth to be moved orthodontically, the force systems acting on the teeth, bracket slot, and wire must be mentally visualised.  Once the force systems have been visualised and understood, actual application of these forces to the teeth can take effect. (Rao, Iskandar, & Mokhtar, 2020, p. 73)  

In current practice, orthodontic training includes some “practice in dental school laboratories and dental hospital clinics” with some also from e-learning (p. 75).  There is preclinical training, clinical training, and apprenticeship.  Even so, there is insufficient customization to the learning, and learners would benefit from increased feedback.  
 



Figure 3:  Orthodontics (by MarCuesBo on Pixabay) 


The coauthors suggest that mobile augmented reality (MAR) may be a solution, with the “AR” described as “a feature-rich interface that adds 3D, textual, and haptic sensing abilities to any learning content” (Rao, Iskandar, & Mokhtar, 2020, p. 76). They conceptualize a behind-the-scenes intelligent support system that can provide necessary feedback and assess competence (p. 77).  There are a number of pages spent describing this proposed system in idealized terms, but this reads more like a desired functions list than anything instantiated.  The core components of the “proposed orthodontic learning system” includes “deliberate practice, collaborative learning, personalisation, ubiquitous learning, (and) feedback and formative assessment” (p. 78).  One visual shows an image of how to put in a nasogastric tube into what looks like a physical mannequin (p. 79).  Another visual depiction shows a conceptualized AR context with voice guidance (p. 80).  Another depiction shows an AR-visual enhanced manipulation of a mirror and another device to prepare a dental cavity (p. 81).  Some of the images look somewhat unwieldy. And the brainstorming seems to begin with the core capabilities of MAR systems, described as  “image recognition, interactive controls, and computer graphics”(p. 83) and built into various handheld or desktop devices, head-mounted displays, projectors, glasses, and others.  Starting from scratch clearly means R&D and expense and expertise, but building on extant platforms with available hardware and software would be more typical for a higher education context.  

This work does acknowledge some limitations, such as a lack of a strong theoretical foundation for integrating MAR into orthodontic training, a lack of general knowledge, a dearth of research in the space.  Current practice relying on tutors in the UK to evaluate orthodontic learners is another barrier (Rao, Iskandar, & Mokhtar, 2020, p. 88).  Still, this work serves as a public call about the need for such learning resources, if those in the private sector may want to explore.  

Supporting the Work of Physical Therapy in Acute Care Settings


Benjamin Just and Kay K. Seo’s “Creating a Computer Simulation with Ill-Structured Problems for Physical Therapists in the Acute Care Setting” (Ch. 4) begins with the researchers engaging ten physical therapists in four urban Midwestern hospitals in interviews to better understand some of the ill-structured problems they face in acute care settings.  From these interviews, they learned of various patient needs and the work of physical therapists to support them even while facing “system factors outside of their control” (p. 104).  From this phenomenological study, the researchers defined some ill-structured problems new physical therapists can be expected to face and harnessed these into computer simulations to enhance their critical thinking and clinical reasoning skills.  

An ill-structured problem vs. a well-structured problem depends on “how many elements of a problem are known, how many rules or principles must be applied, and the number of possible solutions that exist” (Jonassen, 2000, as cited in Just & Seo, 2020, p. 106). Also, the number of variables in the problem or its complexity also is important.  Third is how abstract the problem is or how domain-specific the issue is in terms of its situatedness (p. 106).  Problem-solving involves achieving a particular desired end state to resolve the issue, whether ill- or well-structured.  In every problem context, there is known and unknown information, and there are known and unknown path sequences to arriving at a possible solution.  

In this work, the researchers worked on helping learners develop schemas of common challenges in their field and to engage in various forms of case-based reasoning (applying learning from prior cases to new ones). (Just & Seo, 2020, p. 108) For ill-structure problem solving, common steps include the following five:  “problem representation, solution development, solution justification, solution selection, and solution evaluation” (p. 110).  Various learning aids like cognitive scaffolding, prompts, and other supports may be provided. This work includes descriptions of the various types of ill-structured problems that physical therapists face, “with almost every patient intervention” such as medical instability and old age and illness (p. 115), lack of motivation (p. 116), discharge decision challenges (pp. 116 – 117), intercommunication challenges (p. 117), patient availability given busy care schedules (p. 118), hospital productivity requirements of physical therapists, public relations (p. 119), and others.  The physical therapists with less than six years of experience focused more on challenges in the room with the patient; those with more than six years of experience “identified challenges related to operations at the facility level such as communication and availability” (p. 121).  

The various challenges were ordered by level of difficulty; the designs focused on the authenticity of the cases.  Collecting information from practitioners in a phenomenological study helps acquire information closer to practice and to reality, for computer simulations. 

Cesim™  Global Challenge and Business Simulations


Andres Aguilera-Castillo, Mauricio Guerrero-Cabarcas, Camila Andrea Fúquene, and William Fernando Rios’ “Simulations in Business Education:  A Case Study of Cesim™ Global Challenge” (Ch. 5) suggests that more time spent in a business simulation leads to improved results in managerial soft skills, among undergraduate learners in an international business program in Bogota, Colombia.   The point of the game is to collaborate on teams to create a simulated company that manufactures and distributes mobile phones.  They write:  
 
In order to achieve this, team members had to solve problems and make decisions in essential processes of the company’s value chain, such as production, demand, logistics, finance, human resources, taxes, and research and development. Teams had to compete against each other to achieve the highest cumulative total shareholder return (CTSR), which is the default winning criteria within the simulation (Aguilera-Castillo, Guerrero-Cabarcas, Fúquene, & Rios, 2020, p. 130).  

This work shares some screenshots of the licensed simulation.  Much of this seems related to deciding on inputs and other parameters to the fictionalized company, but hidden computations for the company outputs and performance.  They debrief some of the various elements such as the technological appeal of the product; the elasticity of price, advertising, social responsibility, and number of mobile phone features (p. 139); human resources considerations; research and development (R&D); marketing; logistics (p. 140); finance (p. 141); and others.  They describe the deployment of the simulation over three semesters and 222 students, and then their research for outcomes.  Practice rounds were found to be helpful for the trying of alternate strategies for more optimized outcomes (p. 144).  They close the work with reasoned recommendations.  

Discrete-Event Simulation in Business Education


Marijana Zekić-Sušac, Adela Has, and Marinela Knežević’s “The Use of Discrete-Event Simulation for Business Education:  Learning by Observing, Simulating and Improving” (Ch. 6) is a work based out of a Croatian institution of higher education. They set up a learning experience known as “LOSI” or “learning by observing, simulating, and improving,” and then they assessed student reaction to this approach using a Technology Acceptance Model (TAM) approach.  In a 2018 – 2019 class, the researchers took the following LOSI steps:  preparation of the students for the simulations and field teaching, the “field-teaching phase (active observing of real-life processes)” at companies, the simulation-modeling phase (in which students went to computer labs to design simulation models with graphical flowcharts in Arena Simulation) (p. 163),  and student analyses of simulation results based on different scenarios in order to make improvements to business processes (p. 164).  

The researchers assessed the learning outcomes, which included using the proper terminology for simulations, describing the steps of the simulation-modeling process, selecting suitable methods for simulation modeling of business processes, creating a simulation model and analyzing the results and articulating them, and understanding how to apply simulation modeling (p. 164).  The researchers studied the ease of use, usefulness, enjoyment  in the use of the technology, and the intention to use in the future, as inspired by the Technology Acceptance Model (TAM) (p. 167). In general, the ease of use, usefulness, and enjoyment of the teaching approach ranked with “high average scores,” but the intention to use the approach was evaluated with “lower average scores” (p. 168), which the authors interpret as possibly due to the rarity of simulation modeling in Croatian companies (p. 169).  

A discrete simulation is generally comprised of an “entity, event, activity, and process” (p. 161).  The various discrete-event simulations created during this course included that of the following:  “natural-gas-supply application,” “wine-production processes in the winery,” pizza production, cheese-pie production, sales in a food production company, the address of customer complaints, credit application processes, and investment application processes (p. 172).  

[It seems that these “simulations” are more related to business process modeling and the drawing of flowcharts.  There seems to be some level of what is known as SIPOC modeling or the analysis of “suppliers, inputs, process, outputs, and customers” and the various inputs and outputs for particular services…and the identification of spaces where efficiencies may be achieved.]  

The researchers identified the finding that students found LOSI “easy to use, useful in achieving learning outcomes, and highly enjoyable” (p. 159) 

Learning Language through Knowledge Co-Construction in Minecraft


Joeun Baek, Hyekyeong Park, and Ellen Min’s “Designing a Minecraft Simulation Game for Learning a Language through Knowledge Co-Construction” (Ch. 7) describes the design, creation, and testing of a game with learning based on various individual and group quests in an MMORPG approach.  It does sound like there is a fairly high learning curve to play, with game actions including “gathering information, decorating, crafting, buying, selecting, dialoguing, quizzing, (and) hanging around” along with basic navigation and intercommunications (p. 202).  Certainly, Minecraft has a large user base, and it has been used by many for teaching and learning, with learners creating objects, mapping, journaling, building social skills, virtual world building, and others.  The game itself has both a creating mode and a survival one (where the playable characters are under risk).  And as described, the world has four themes:  “Landmarks in the World, Having Fun in an Amusement Park, Attending a Party at a Friend’s House, and Designing a Share House” (p. 182).  

Here, the team was informed by two main frameworks:   Robert M. Gagné’s nine events of instruction and Bernd H. Schmitt’s “strategic experience modules”.  Gagné’s nine events focus on the following nine elements (in general sequence):  gaining the attention of players with a stimulus that engages their minds,” defining objectives, stimulating recall of prior learning, presenting the content, “providing learning guidance through additional examples and other supportive materials,” “eliciting performance or practicing,” providing “immediate and specific” feedback, assessing performance, and “enhancing retention and transferring skills and learning for future application” (Baek, Park, & Min, 2020, pp. 188 – 189).  




Figure 4:  “Minecraft” (by SauerC on Pixabay)


The other model that this team built their design on suggests five “strategic experience modules” (SEMS) (for marketing), which might suggest something about “sell” in teaching and learning.  The five experiences are the following:  “sensory experiences (Sense), feel experience (Feel), think experience (Think), act experience (Act), and relate experience (Relate)” (Schmitt, 1999, as cited in Baek, Park, & Min, 2020, p. 191), based on a book by Bernd H. Schmitt in 1999.  The appeal has to be on one or more of the target person’s five senses, with an elicitation of positive feelings, an appeal to think creatively for a potential “shift of their opinions,” an action or behavior change, and then helping “customers to feel connected to a certain message” for experiential marketing (p. 191).  Different appeals are created for different target audiences.  This SEM approach was applied to a creative exercise of room building in Minecraft, first collaboratively and then individually, and other in-world tasks of wayfinding and mapping and quest completing (with accompanying designed activity flows).  

In their respective gameplay quests, learners simultaneously negotiate “unfamiliar words or phrases” and co-create new knowledge, which seems more like an incidental focus than a central one.  While there is ludic pleasure, there is also quizzing and assessment (p. 184).  The coauthors share screenshots of some of the designed virtual game spaces on Minecraft.  

These researchers also conducted pilot testing by implementing the simulation game and analyzing data, gameplay video, interviews of participants, and other data sources (p. 201).  They observed the need for “more conditionals and loops in order for players to repeat their simulation game at any place and time” (Baek, Park, & Min, 2020, p. 181).  From the outside, it is unclear how much language acquisition occurs with so much focus and cognitive attention on the game.  

3D Simulation to Teach Functional Skills for Learners with Varied Disabilities 


In a typical approach, versioning learning for those with different disabilities means offering multiple perceptual channels to access to contents.  Often, it means offering versions in simpler technologies (such as video -> text, audio -> text).  In the case of Maria-Ioanna Chronopoulou and Emmanuel Fokides’ “Using a 3D Simulation for Teaching Functional Skills to Students with Learning, Attentional, Behavioral, and Emotional Disabilities” (Ch. 8), the direction seems to go the other way—to 3D.  This study was based on an A-B single-subject study design in which learners were presented with 3D simulations and asked to share what they learned and demonstrate the new behaviors; this study involved only eight 8-9 year olds, with varying disabilities, and included in mainstream general education classrooms (instead of being separated out).  Their differing needs are addressed with structured programmatic interventions.  An important learning track involves the acquisition of functional living skills for those with “learning and mental disabilities, developmental disorders, psychological or emotional disorders, and motor or sensory impairments…” and “autism spectrum disorders” (Chronopoulou & Fokides, 2020, p. 211) and ADHD (p. 212).  This work explored the use of a 3D simulation approach to learners with “mild disorders (i.e., learning, attentional, behavioral, and emotional disabilities)” to help them attain functional skills in the school context (p. 213).  Each of the research participants is described lightly based on their diagnoses and observed behaviors in the classroom (pp. 214 – 215).  

The technology underlying the computational simulations was OpenSimulator.  A virtual school space was created, and non-playable characters acted as “students…and guides/teachers” (Chronopoulou & Fokides, 2020, p. 215).  Some 50 hours went into the development of the simulations.  A teacher would greet the children as they came to each area, and this character would explain the expected behaviors. The various other NPC avatars modeled expected behaviors in the respective contexts.  There was a tell-and-show dynamic.   The research found the simulations to be effective for this target group of learners based on semi-structured interviews and observations, among others.  (Given the vulnerability of the learners, the research went through IRB oversight and required parent / guardian consent in order to run the research and to access school records of the children.)  The co-researchers suggest that 3D simulations may be practical and efficacious in some learning contexts for young learners with disabilities, with their research as a proof of concept.  

Simulated Roleplaying National Leaders and Heads of Terror Groups for Learning about Terrorism


Mat Hardy and Sally Totman’s “Teaching about Terrorism through Simulations” (Ch. 9) describes a role-playing exercise that has been used for more than 25 years to help students understand the complexities of geopolitics and the resorting to terroristic threats and violence to achieve particular political aims.  The coauthors note that the 9/11 attacks in 2001 and the resulting War on Terror raised broad learner interest in the topic.  An effective student of terrorism has to be able to get beyond their own local cultural perspectives, Hollywood-types of superficial understandings of terrorism, and be able to work through huge volumes of published research on the topic.  An in-depth roleplay enables vicarious experiential learning by doing and the harnessing of the human imagination.  

One focal roleplay involves the Middle East Politics Simulation (MEPS) at Deakin University, which is run twice annually, and uses an HTML interface 9built as part of a computer science student’s Honors project) (Hardy & Totman, 2020, p. 242).  Learners take on the roles of various country leaders in the Middle East and also as terrorist group leaders (including those from Islamic State, Al-Qaeda in the Arabian Peninsula, Al-Qaeda in the Islamic Maghreb, Hamas, Hezbollah, (and) the PKK) (p. 243).  Various scenarios have been ripped from the headlines and used as the contexts in which the various learners follow through in-character, with various strategies and tactics.  The idea is to get beyond simple understandings and to achieve a more real-world awareness.  The empathy for why particular individuals may take particular courses is not to encourage their over-empathizing but to help students take into consideration various points of view that may help inform possible solutions.  

The coauthors also point to some strategy in letting students take the lead on their research and character development.  

A student-driven approach also goes some way to alleviating another of the tensions described earlier:  the implied pressures felt by teachers regarding what they present on terrorism and how this might be construed as supportive of radical causes.  The students in a role play will need to research their own roles, removing the need for the teacher to ‘lecture’ about the topic and have this material ascribed to them.  The experiential learning cycle offers a deeper level of insight than a standard lecture approach can and allows students to form their own opinions.  (Hardy & Totman, 2020, p. 250) 

Certainly, it makes sense to consider the real world even in the relative “safety” of the classroom.  This work includes research of achieved learning post-simulation, augmented with quotes from the respondents.  


Evaluating Computer-Based Simulacrum for Learning


How does one know a computer simulation has been effective for learning?  How can relevant learning frameworks and models be harnessed for such an evaluation?  And how can the evaluation tool be made sufficiently general to apply to a variety of simulations (since these are so diverse in creation, implementation, and approach—such as across different disciplines and domains)?  Is a quality computer simulation about fidelity to what it is modeling?  Is a computer simulation a quality one if it addresses emotional experiences appropriately (such as by engaging the affective domain)?  Is it about how the instructor uses particular simulations in the teaching and learning context?  

Wendi M. Kappers’ “Shaping an Evaluation Framework for Simulations:  A Marriage Proposal” (Ch. 10) suggests bringing together various theories and Bloom’s Taxonomy to create a matrix analysis of the respective simulations.  Her approach is informed by Contextual Learning Theory, Vygotsky’s Social Development Theory, and Kolb’s Experiential Learning Theory (Kappers, 2020, p. 265), with a focus on evidence-based learning, and Bloom’s Taxonomy (p. 267).  Instructional design practices also infuse her approach, namely the idea that course design (“modules, expected outcomes, content, activities/tasks, and assessment”) should work holistically towards achieving the defined learning outcomes (Kappers, 2020, p. 269), across disciplines. The author proposes a “marriage” between the framework and the taxonomy for instructional designers and educators, including the subject, the (revised) Bloom’s classification levels, and a “purposed-based simulation taxonomy” (including focuses on modeling, tasks/skills, and problem-solving) (Kappers, 2020, p. 272).   This work shows the challenges of wrangling complex issues from challenging and varied practices and a broad research literature.  

Conclusion


Yufeng Qian’s Teaching, Learning, and Leading with Computer Simulations (2020) focuses on practical and theory-informed ways to approach the design, development, implementation, and assessment of computer simulations for learning around the world.  The respective works are well researched and have valuable ideas for practice.  The inclusion of visuals enhances the readability of the text.  
  





About the Author


Shalin Hai-Jew works as an instructional designer / researcher at Kansas State University.  Her email is shalin@ksu.edu.  

Thanks to IGI Global for a watermarked review copy of the text.  

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