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In this study, we assessed a highly structured, yearlong, case-based course designed for undergraduate pre-health students. We incorporated both content learning assessments and developed a novel method called Multiple Mini Exams for assessing course impact on the development of skills that professional schools often seek in pre-health students, focusing on students' abilities to collaborate with others, display bedside manners, synthesize patient case details, appropriately use scientific and medical language, and effectively attain patients' medical histories. This novel method utilized a rubric based on desired medical student skills to score videotaped behaviors and interactions of students role playing as doctors in a hypothetical patient case study scenario. Overall, our findings demonstrate that a highly structured course, incorporating weekly student performance and presentation of patient cases encompassing history taking, diagnosis, and treatment, can result in content learning, as well as improve desired skills specific for success in medical fields.

The current and ongoing challenges brought on by climate change will require future scientists who have hands-on experience using advanced molecular techniques, can work with large data sets, and can make correlations between metadata and microbial diversity. A course-embedded research project can prepare students to answer complex research questions that might help plants adapt to climate change. The project described herein uses plants as a host to study the impact of climate change-induced drought on host-microbe interactions through next-generation DNA sequencing and analysis using a command-line program. Specifically, the project studies the impact of simulated drought on the rhizosphere microbiome of Fast Plants rapid cycling "Brassica rapa" using inexpensive greenhouse supplies and 16S rRNA V3/V4 Illumina sequencing. Data analysis is performed with the freely accessible Python-based microbiome bioinformatics platform QIIME 2.

The ubiquity and ease with which microbial cells disperse over space is a key concept in microbiology, especially in microbial ecology. The phenomenon prompted Baas Becking's famous "everything is everywhere" statement that now acts as the null hypothesis in studies that test the dispersal limitation of microbial taxa. Despite covering the content in lectures, exam performance indicated that the concepts of dispersal and biogeography challenged undergraduate students in an upper-level Microbial Ecology course. Therefore, we iteratively designed a hands-on classroom activity to supplement the lecture content and reinforce fundamental microbial dispersal and biogeography concepts while also building quantitative reasoning and teamwork skills. In a class period soon after the lecture, the students formed three-to-five-person teams to engage in the activity, which included a hands-on dispersal simulation and worksheet to guide discussion. The simulation involved stepwise neutral immigration or emigration and then environmental selection on a random community of microbial taxa represented by craft poms. The students recorded the results at each step as microbial community data. A field guide was provided to identify the taxonomy based on the pom phenotype and a reference to each taxon's preferred environmental niches. The worksheet guided a reflection of student observations during the simulation. It also sharpened quantitative thinking by prompting the students to summarize and visualize their and other teams' microbial community data and then to compare the observed community distributions to the idealized expectation given only selection without dispersal. We found that the activity improved student performance on exam questions and general student satisfaction and comfort with the biogeography concepts. Activity instructions and a list of needed materials are included for instructors to reproduce for their classrooms.

The challenge of creating reliable technology-based resources for science learning is a perennial challenge in Philippine education, with limited learning materials accessible to all learners. This study is about the development of a videocast embedded with physics education technology (PhET) simulation that served as supplementary learning material for grade 9 science in response to the scarcity of dependable visualization materials. The study employed the developmental research design with analysisdesign-development-implementation-evaluation (ADDIE) model as the developmental framework. The vodcast evaluation tool, achievement test questionnaire, and vodcast perception survey questionnaire for students and teachers were used in the data collection, while the Kendall's W statistic, mean, percentage, and gain score were used in the data interpretation. The teacher respondents (N=64) have moderate agreement on the ranking of topic difficulty, with Kendall's W of 0.45. The researcher-made vodcast attained an overall rating of 4.78 from experts, which implies that the vodcast can be very good material for classroom implementation. The developed achievement test has acceptable difficulty and discrimination indices. The implementation stage yielded a low normalized gain, which can be accounted for by unfocused attention during the pandemic. Nevertheless, the voicecasts were found very useful in learning projectile motion, as perceived by both students and teacher-observers.

High school graduation is a pivotal milestone that can shape students' future, offering them opportunities for higher education and gainful employment. Because research shows grade point averages and course failures to be predictive of high school graduation, it is important for students' life outcomes that their teachers assign them equitable grades. However, recent research has scrutinized how schools have traditionally graded students, calling for new approaches such as minimum grading. In this analysis, we simulate the economic impacts of implementing a minimum grading policy statewide during the ninth-grade year of the cohort of students who were in ninth grade in 2015-16 in Arkansas. On average, in Arkansas public schools, we estimate that minimum grading would affect about one (narrow bound) to 3%(broad bound) of students, increase cost-effectiveness by 6% (narrow bound) to 23% (broad bound), largely varying across districts, and have essentially no impact on the return on investment. The application of minimum grading shifted 1% of failing course grades to passing, thereby positioning 10% of previously failing students to pass. These findings suggest that minimum grading could serve as a cost-effective strategy to enhance graduation rates in districts with higher rates of affected students, without necessitating additional educational spending.

In response to the adoption of Agile practices and processes by businesses, IT/IS educators are working to add Agile content to their courses. Teaching students about Agile involves teaching them about the history, mindset, and values of Agile, along with an introduction to the practices and processes used in an Agile product. Along with this, it is essential that students gain experience using Agile in a project setting. This paper discusses an Agile practice project where students use all aspects of Agile to address a problem and build a solution using Legos. The use of Legos, along with a project that students can easily see themselves using, the practice project allows students to focus on developing their Agile skills and mindset. The project serves as a useful transition from traditional classroom instruction about Agile to a project for a real-world client.

This paper presents the results of a multi-year effort to redesign the introduction to business course at Western Michigan University. ScrimmageSIM, a business simulation that emulates commercial ERP systems, provides the core experience in the course and is a mechanism for students to develop their understanding of business with a focus on quantitative analysis. The design and implementation of the simulation experience follows the experiential learning spiral, as students run the simulation five times with increasingly complex scenarios. The overall design of the course is competency-based, as students have the opportunity to redo many of the course assignments to earn a better grade. The simulation experience, combined with the competency-based design of the course, has resulted in a more rigorous course with students earning grades that are better than they were with the previous curriculum.

This research aims to compare the ability and item parameter estimations of Item Response Theory according to Maximum likelihood and Bayesian approaches in different Monte Carlo simulation conditions. For this purpose, depending on the changes in the priori distribution type, sample size, test length, and logistics model, the ability and item parameters estimated according to the maximum likelihood and Bayesian method and the differences in the RMSE of these parameters were examined. The priori distribution (normal, left-skewed, right-skewed, leptokurtic, and platykurtic), test length (10, 20, 40), sample size (100, 500, 1000), logistics model (2PL, 3PL). The simulation conditions were performed with 100 replications. Mixed model ANOVA was performed to determine RMSE differentiations. The prior distribution type, test length, and estimation method in the differentiation of ability parameter and RMSE were estimated in 2PL models; the priori distribution type and test length were significant in the differences in the ability parameter and RMSE estimated in the 3PL model. While prior distribution type, sample size, and estimation method created a significant difference in the RMSE of the item discrimination parameter estimated in the 2PL model, none of the conditions created a significant difference in the RMSE of the item difficulty parameter. The priori distribution type, sample size, and estimation method in the item discrimination RMSE were estimated in the 3PL model; the a priori distribution and estimation method created significant differentiation in the RMSE of the lower asymptote parameter. However, none of the conditions significantly changed the RMSE of item difficulty parameters.

Simulation has been recognized for its ability to develop competency-level skills and as a replacement for some introductory fieldwork (FW) hours. This study explored how occupational therapy competency-related skills developed over sequential in-person simulations across health practice contexts during Level 1 FW. Entry-to-practice occupational therapy students (N = 66) participated in six sequential, formative, Level 1 FW simulations. The first three sequential simulations (the same patient case evolves in each successive interaction) included a trained simulated patient in a community mental health context and the following three engaged a trained simulated inpatient in a physical health context. Evaluation rubric variables included selected Competencies for Occupational Therapists in Canada (2021) scaffolded to performance expectations at an introductory Level 1 FW placement level. Quantitative pre-post comparison design with secondary data analysis was analyzed using Wilcoxon signed-rank test and ordered logistic regression. Each additional simulation demonstrated significant increases in the odds of improved performance in clinical skills, clinical decision making, responding to evolving patient's needs and priorities, identifying their own strengths and weaknesses, articulating clinical reasoning, and receiving constructive criticism. However, students' skills in the physical health context for decision-making and responding to the patient's needs and priorities did not demonstrate the same improvement trajectories as the mental health context. Sequential simulations are an effective modality for developing Level 1 competency related skills in different practice contexts. Depending on the competency-related practice skill and context, three or more formative unfolding simulations in that context may be needed for a significant improvement.

Standardized patient encounters are being utilized more often in occupational therapy education as a replacement for traditional fieldwork. While there is a growing body of research to support the use of this model in developing student skillsets and confidence, there remains limited information on the topic, and no studies which look at its use with occupational therapy assistant students. Twenty-four occupational therapy assistant students participated in standardized patient encounters which served as a replacement for traditional Level I fieldwork. All students completed an anonymous supplementary course evaluation regarding their experiences. A secondary analysis of the data looked at their perceptions of a standardized patient encounter model for fieldwork and how it did or did not prepare them for future Level II clinicals. Quantitative and qualitative data exposed aspects of these experiences which students found to be most and least effective. Overall, data showed moderate support for use of standardized patient encounters to support student confidence and skills in anticipation of Level II fieldwork. The student perception of these types of experiences is influenced by environmental (e.g., structure) and personal (e.g., student personality) factors. Success requires adequate preparation of all involved parties. Use of standardized patient encounters should be researched further to determine its impact on fieldwork performance evaluation scores and future employment.

Context: This study is about the teaching method of simulation exercises and is set in a police education context. Simulation exercises are a central part of Swedish police education, and therefore it is of interest to explore how they are used, and for what purpose, by investigating police teachers' perceptions of this teaching and learning method. Police teachers are police officers who work as teachers at a police education unit on contracts lasting a few years, but which can be extended, and they usually lack any formal pedagogical training. Approach: In this study, the exploration of the use of simulation exercises was conducted through an inductive approach which included semi-structured interviews with 12 police teachers. The analysis was carried out in several steps. To promote impartiality in the initial data analysis the researcher first stayed close to the data and connection with the findings of previous studies was only considered in the latter stages of this analytic process. Findings: The findings show that the police teachers perceive that the overall purpose of simulation exercises is for students to apply specific content taught in courses, both physical techniques and methods, and more theoretical knowledge, in the fluid context of scenarios relevant to police work. The results also show that the teachers are aware that the purpose of the exercises is stated in the planning documents, but because they inherit the designs from previous teachers, they may not be aware of the underlying details of it or what is to be achieved in the scenario. The findings also demonstrate that the teachers learn the craft of designing and performing simulation exercises and develop their roles as teachers through an informal workplace learning process that involves tacit knowledge developed through working together, and by talking to and observing each other. Conclusion: The paper contributes to the field of simulation exercises in vocational (higher) education in that the findings can provide educated arguments for the need for scholarly discussions on simulation exercises as a pedagogical tool that supports student learning, as well as arguments for why formal pedagogically-oriented continuing education on the design and implementation of simulation exercises where learning is in the foreground may be needed to support police teachers' professional development.

Due to advancements in medical science leading to increased life expectancy, the number of older adults is on the rise. Empathy is crucial in catering to the unique needs of this vulnerable population. The use of geriatric simulation suits to cultivate empathy among health science students is gaining traction. Nevertheless, the efficacy of this teaching approach remains unexplored among occupational therapy students. We recruited a convenience sample of 21 occupational therapy graduate students for a mixed methods study. Participants engaged in a two-hour session during which they performed daily tasks like meal preparation, laundry, and dressing while wearing various components of a geriatric simulation suit. Empathy levels were evaluated before and after simulation using an abridged and modified version of the Comprehensive State Empathy Scale. Participants engaged in focus group discussions regarding their experiences with using the geriatric suit. Thematic analysis was employed to analyze the qualitative data. A significant rise (p<0.001) in mean empathy scores following geriatric simulation was noted. Three main themes and nine sub-themes emerged from the focus group discussions, indicating that participants gained a deeper understanding of the challenges encountered by older adults and demonstrated greater empathy towards them. The findings of this study address the existing gap in literature, demonstrating that geriatric simulation is an effective method for promoting empathy towards older persons among occupational therapy graduate students.

Early mobility in the Intensive Care Unit (ICU) can improve a multitude of patient outcomes, and occupational therapists (OTs) play a valuable role as part of the interprofessional team, with the ability to address activities of daily living, functional cognition, psychological and communication needs, and more. In 2022, the first iteration of an ICU interprofessional education simulation (Sim-IPE) yielded poor outcomes for OT students. This study aimed to modify existing pre-learning activities in the Sim-IPE's second iteration to improve OT students' perceptions and professional role awareness in interprofessional ICU care. Students from Doctor of OT, Bachelor of Science Nursing, Doctor of Physical Therapy (PT), and Associate Program Respiratory Therapy programs from one university participated in an ICU Early Mobility Sim-IPE with enhanced pre-learning activities and environmental modifications targeting OT student outcomes. Investigators employed a mixed methods approach, including pre/post quantitative analysis through the SPICE-R2 instrument and qualitative analysis of OT students' written reflections. Quantitatively, OT students (n = 12) demonstrated significant improvement in SPICE-R2 scores from pre- to post-Sim-IPE, as well as significant improvements when compared to OT student scores from the first iteration. Qualitatively, OT students reflected improved role awareness when compared to OT students from the first Sim-IPE, however, continue to struggle with role assertion and ambiguity, particularly with PT students. This study improved the OT students' Sim-IPE experience; specifically, role awareness and perceptions of interprofessional practice. Residual challenges in role assertion and ambiguity offer opportunities for future intervention and research.

The use of high-fidelity simulation and standardized patients (SPs) in occupational therapy (OT) education is expanding. However, the implementation of simulation varies across programs, leading to inconsistent outcomes and research limitations. Furthermore, details on SP use and training are lacking in OT literature. This article aims to provide OT educators with considerations for improving simulation fidelity by effectively using highly trained SPs. For example, recruiting SPs from diverse backgrounds is necessary to improve sociological fidelity, and proper training of SPs is required to ensure psychological fidelity. This article also emphasizes the need for standardized training for SPs and recommends following the Association of Standardized Patient Educators (ASPE) guidelines to ensure best practices in OT education. Adequate SP training and ongoing professional development are essential for maintaining simulation fidelity during SP experiences and optimizing student learning outcomes. Implementing SP experiences within the OT curriculum, SP recruitment and training, case development, pre-briefing, and debriefing processes are discussed, with recommendations from current evidence and the authors' experience at an institution accredited by the Society for Simulation in Healthcare. Trained SPs can enhance simulation fidelity and provide students with realistic and compelling learning experiences, better preparing them for fieldwork and clinical practice. While further research is needed to explore the efficacy of SP encounters in OT education and the student experience, this article reinforces the need to standardize the use and training of SPs to enhance simulation fidelity and support the reliability and validity of future research efforts surrounding the use of SPs.

Building on previous research that has demonstrated close connections between constructivism, technology, and artificial intelligence, this article investigates the constructivist underpinnings of strategically integrating GenAI experiences in higher educational contexts to catalyze student learning. This study presents a new model for leveraging GenAI tools, for individualized, formative, peer-simulated feedback in graduate-level courses in higher education. This exploratory study presents graduate student reflections about the process and product created using ChatGPT for formative feedback with an instructor-generated prompt for an organizational behavior course. An analysis of student reflections and examples of ChatGPT-generated peer-simulated feedback, as well as an examination of ethical considerations, offer insights into the learning potential of utilizing GenAI tools for peer-simulated feedback in graduate-level courses.

Cognitive dissonance is an important element in adult learning in that it challenges previously held ideas in favor of new knowledge. In-class simulations and game-based learning are used as innovative and effective pedagogical tools in challenging adult learners and enhancing the students' ability to think critically about larger societal needs. This paper will review the literature relevant to cognitive dissonance, adult learning, and game and simulation practices in higher education. The authors present the results of one simulation activity in a quasi-experimental non-random comparison group conducted across five universities within multiple undergraduate and graduate level social work policy courses. Findings of this research on the use of simulations in social work policy courses can be used to guide other social work programs with embedding this effective educational practice into their programs. Institutions of higher education, specifically within the discipline of social work, can play an important role in continuing the research and evaluation of this effective pedagogical practice through measuring outcomes on student critical thinking and changes in student beliefs and biases.

This review explores the integration and effects of the Internet of Things (IoT) in education, highlighting its importance in transforming traditional teaching and learning techniques. It examines the early uses and historical growth of IoT, its development, and the turning points in its adoption. It explores IoT platforms, tools, and technologies in education, including wearables, smart devices, augmented and virtual reality, gamification, and collaborative learning. It discusses the role of IoT in improving campus management, including intelligent campuses with IoT-enabled infrastructure, energy-saving technologies, and safety and security improvements. The study discusses data security and privacy issues in IoT installations and the ethical and legal implications of data collection in the classroom. The study also discusses upcoming trends and prospects for IoT usage in education, including AI and machine learning integration. Finally, the review provides insights for educators, decision-makers, and stakeholders, identifying research gaps and recommending areas for future IoT implementation.

The design case details the collaborative work of a design team--three faculty members, one instructional designer, and one educational resource specialist--to create a simulation-based interprofessional education (IPE) experience for future healthcare professionals. Before the COVID-19 pandemic that caused the shutdown of campuses across the country/world, this simulation-based learning experience was always offered in a face-to-face format. Thus, this case highlights the challenges and opportunities of designing this online learning experience within a limited period of time. Further, this case documents what theories or evidence-based practices were instrumental in designing this learning experience, along with the design team's narrative regarding key design decisions and moves. It also includes a design narrative focusing on the description of the design process, such as key design judgments, decisions, and concrete examples of the design process outcome. Lastly, the design case highlights unique design features: Scalability of instruction through accessibility and usability, authenticity, interprofessional collaboration, and reflection. The design was guided by the TEACH (Team Education Advancing Collaboration in Health) core curriculum in the state of Indiana that foregrounds interprofessional practice competencies and teamwork in preparing future healthcare professionals.

The COVID-19 pandemic has had a significant impact on high-stakes testing, including the national benchmark tests in South Africa. Current linear testing formats have been criticized for their limitations, leading to a shift towards Computerized Adaptive Testing [CAT]. Assessments with CAT are more precise and take less time. Evaluation of CAT programs requires simulation studies. To assess the feasibility of implementing CAT in NBTs, SimulCAT, a simulation tool, was utilized. The SimulCAT simulation involved creating 10,000 examinees with a normal distribution characterized by a mean of 0 and a standard deviation of 1. A pool of 500 test items was employed, and specific parameters were established for the item selection algorithm, CAT administration rules, item exposure control, and termination criteria. The termination criteria required a standard error of less than 0.35 to ensure accurate abilities estimation. The findings from the simulation study demonstrated that fixed-length tests provided higher testing precision without any systematic error, as indicated by measurement statistics like CBIAS, CMAE, and CRMSE. However, fixed-length tests exhibited a higher item exposure rate, which could be mitigated by selecting items with fewer dependencies on specific item parameters (a-parameters). On the other hand, variable-length tests demonstrated increased redundancy. Based on these results, CAT is recommended as an alternative approach for conducting NBTs due to its capability to accurately measure individual abilities and reduce the testing duration. For high-stakes assessments like the NBTs, fixed-length tests are preferred as they offer superior testing precision while minimizing item exposure rates.

Educators, including English Language Teaching practitioners, acknowledge the influence of collaborative learning on students' learning experiences, as demonstrated by numerous studies conducted in diverse contexts. This research, however, keeping instructional innovation, students' collaborative engagement, language learning and classroom dynamics especially in the context of an Arab university where such studies are limited, examines the effect of a collaborative learning intervention program on EFL students' English learning and social interactions in terms of teamwork, peer learning, and social intelligence. To achieve the study objective, the quasi-experimental design with two groups (experimental and control) was employed. The study was applied to a sample of prep-year university students who were randomly divided into two groups: control and experimental. While the experimental group studied English using collaborative learning skills, the control group studied following traditional ways of teaching. Both groups were assessed using a pre-and post-test (performance test) and an assessment card (social learning). In addition, teachers were interviewed about their views on how collaborative learning can strengthen EFL students' social learning success. The result revealed statistically significant differences between the scores of the control and experimental groups in favor of the later, indicating that the intervention program highly helped students improve their English learning skills and enrich their social interaction. Finally, the interview analysis highlighted the ways to enhance EFL students' language learning and social interaction through group projects, discussion groups and debates, role-playing and simulations, diverse collaborative learning practices, and effective teacher facilitation. The findings imply that collaborative learning could be a potential treatment to help EFL learners enrich their social learning experience and success. Further research on collaborative learning's extended impacts, teacher readiness, diverse assessment methods, and gender disparities are recommended to address the limitations of the current study.

Various areas of educational research are interested in the transitions between different states--or events--in sequential data, with the goal of understanding the significance of these transitions; one notable example is affect dynamics, which aims to identify important transitions between affective states. Unfortunately, several works have uncovered issues with the metrics and procedures commonly used to analyze these transitions. As such, our goal in this work is to address these issues by outlining an alternative procedure that is based on the use of marginal models. We begin by looking at the specific mechanisms responsible for a recently discovered statistical bias with several metrics used in sequential data analysis. After giving a theoretical explanation for the issue, we show that the marginal model procedure appears to adjust for this bias. Next, a related problem is that the common practice of removing transitions to repeated states has been shown to have unintended side-effects--to account for this issue, we develop a method for extending the marginal model procedure to this specific type of analysis. Finally, in a recent study evaluating the problem of multiple comparisons and sequential data analysis, the Benjamini-Hochberg (BH) procedure, a commonly used approach to control for false discoveries, did not perform as expected. By applying a technique from the biostatistics and epidemiology literature, we show that the performance of the BH procedure, when used with the marginal model method, can be brought back to its expected level. In all of our analyses, we evaluate the proposed method by both running simulations and using actual student data. The results indicate that the marginal model procedure seemingly compensates for the problems observed with other transition metrics, thus resulting in more accurate estimates of the importance of transitions between states.

Researchers have revealed the advantages of experiential learning for students and professionals at all levels of the health care delivery system. The purpose of this study is to determine the effectiveness of the use of head simulators in dental school in acquiring proficient periodontal knowledge, dental skills, and confidence by practicing oral health professionals. Of the 117 purposive sampled participants surveyed using a 5-point Likert scale questionnaire, 60 respondents used head simulators during their dental school education. On the effect of the head simulator enhancing knowledge. The findings regarding the effect of the head simulator in dental school revealed varying perspectives. A significant majority of participants agreed the head simulator had a beneficial effect on their skills. Among these findings, a third of participants strongly agreed the use of the head simulator notably enhanced their skills. When considering the influence on knowledge, the responses were more evenly distributed. Almost 40% of participants agreed the head simulator positively affected their knowledge, while almost 20% of participants generally disagreed. Examining the effect on confidence, findings also depicted varying viewpoints among the participants with 42% acknowledging the head simulator had a positive effect on their confidence. The findings suggest that head simulators positively affect dental education, particularly in enhancing knowledge, skills, and confidence.

The COVID-19 pandemic caused a major disruption to higher education as face-to-face teaching had to shift to distance teaching overnight. In this paper, we describe the adaptation of an operations management undergraduate core module, taught to first-year students, from face-to-face delivery to emergency online delivery. In our online version, we used a mix of traditional and flipped classroom techniques. We adopted a "live" online lecture, where students were encouraged to interact with their instructors and ask questions, and flipped live online tutorials, where students and instructors discussed case studies. In addition, we used a web-based simulation game as a learning and assessment tool. After the simulation game was complete, we assessed our students using a reflective group presentation regarding the decisions they made throughout the game. Based on student feedback, the curriculum design and the module adaptations that we adopted for its emergency online delivery can be considered successful. In particular, students were satisfied with the module quality and structure. Following our experience from adapting our face-to-face module for emergency online delivery, we provide a framework for switching to emergency online teaching along with some useful insights and recommendations to operations management educators.

This paper develops a spreadsheet simulation methodology for teaching simulation and performance analysis of priority queues with multiple servers, without resorting to macros, add-ins, or array formula. The approach is made possible by a "single overtaking" simplifying assumption under which any lower-priority customer may be passed in line by at most one higher-priority customer. By increasing the number of overtaking customers, one at a time, the simulation model is extended to the "multiovertaking" case. These simplifying assumptions make such spreadsheet simulations (of more complex queuing networks) accessible to students, and so the paper includes teaching and learning strategies for the classroom. Performance analysis of single-overtaking versus multiovertaking polices is included.

Background: The teaching and learning of skills in a classroom setting are often thought to require a resource-intensive approach. Purpose: This study explores the impact of a relatively basic and short communication skills teaching session on postgraduate students' self-perception of their skills. Methodology/Approach: Data was gathered using a preteaching and postteaching survey designed to enable students to evaluate their own sense of skill development. Findings/Conclusions: Students overwhelmingly found this teaching session helpful in terms of increasing their confidence and readiness to communicate on their first social work practice placement. Implications: Effective skill development can take place within the constraints of a classroom setting with few resources using a basic simulation within an experiential framework.

This study reports an investigative study with 55 English-major participants in a Chinese university about using simulation in business English correspondence teaching. The study found that participants had strong needs in practical skills development and learning business English correspondence writing. The simulation approach was perceived to be effective and had positive learning outcomes in business communication skills development, motivation, confidence and vocabulary growth, business and language knowledge improvement, and more understanding about the business practice. The constraint factors in simulation included lack of business knowledge and vocabulary, ineffective group cooperation, and lack of understanding about the real-world business background.

The study determined the relative effectiveness of simulation games, blended learning, and interactive multimedia in enhancing learning outcomes in Basic Science of pupils with varying abilities, with a view to providing information on the most effective strategy for instructing Basic Science among pupils with varying abilities. Children should be exposed to and commence learning science at a young age because science and technology are the dynamic forces behind present socioeconomic progress. The research design employed was a quasi-experimental research design. The experiment was conducted in six schools, and two schools were used as the control group. The analysis used descriptive and inferential statistics. Permission was sought from the Local Government Education Authorities (LGEA) to use the schools in their jurisdictions for the experiment. Participants were given a consent form for their parents. Pseudonyms were used to replace participants' names. The findings indicate that interactive multimedia is more effective with pupils in mainstream schools, whereas blended learning proves more effective for pupils in special schools. These findings imply that teachers should employ strategies to captivate and maintain attention while teaching Basic Science.

The network scale-up method (NSUM) is a survey-based method for estimating the number of individuals in a hidden or hard-to-reach subgroup of a general population. In NSUM surveys, sampled individuals report how many others they know in the subpopulation of interest (e.g. "How many sex workers do you know?") and how many others they know in subpopulations of the general population (e.g. "How many bus drivers do you know?"). NSUM is widely used to estimate the size of important sociological and epidemiological risk groups, including men who have sex with men, sex workers, HIV+ individuals, and drug users. Unlike several other methods for population size estimation, NSUM requires only a single random sample and the estimator has a conveniently simple form. Despite its popularity, there are no published guidelines for the minimum sample size calculation to achieve a desired statistical precision. Here, we provide a sample size formula that can be employed in any NSUM survey. We show analytically and by simulation that the sample size controls error at the nominal rate and is robust to some forms of network model mis-specification. We apply this methodology to study the minimum sample size and relative error properties of several published NSUM surveys.

Random forests are a nonparametric machine learning method, which is currently gaining popularity in the behavioral sciences. Despite random forests' potential advantages over more conventional statistical methods, a remaining question is how reliably informative predictor variables can be identified by means of random forests. The present study aims at giving a comprehensible introduction to the topic of variable selection with random forests and providing an overview of the currently proposed selection methods. Using simulation studies, the variable selection methods are examined regarding their statistical properties, and comparisons between their performances and the performance of a conventional linear model are drawn. Advantages and disadvantages of the examined methods are discussed, and practical recommendations for the use of random forests for variable selection are given.

Accomplishing a communication task in the real world requires the ability not only to do the task per se but also to manage aspects of the context in which it occurs. For this reason, simulations of target language use contexts have been incorporated into the design of communicative language tests as a way of enhancing the authenticity of assessment task performance. Although some contextual factors may increase extraneous cognitive load and distract learners from focusing on the task at hand (Sweller, 1994), they represent important design considerations in task-based language assessment (TBLA), where the purpose of assessment is to determine what second language (L2) learners can do with the target language in the real world. In that sense, the extraneous cognitive load might well be part of the construct we are interested in assessing. Accordingly, the current study simulated aspects of a real-world task performance context as part of an email writing task assessment. Simulated context was operationalized as (a) additional information about the task scenario, (b) a visual image to simulate the physical context, and (c) an audio to replicate the real-world experience. A total of 276 L2 English learners performed the email task, half with simulated context and the other half without it. Findings revealed that, when presented with simulated context, the tasks were perceived by participants to have induced more time pressure and to be more interesting. In terms of performance effects, the provision of simulated context negatively affected the syntactic complexity of participants' writing but positively affected their syntactic fluency. It also led to greater discrimination among learners at different proficiency levels on various measures of language performance. The paper concludes by highlighting implications for task design and validity evaluation, especially in TBLA.

Context: Simulations and standardized patient encounters (SPEs) have been increasingly used in professional athletic training programs. Recently they also have been identified as a mechanism to assess curricular content standards. Objective: To investigate how professional athletic training programs use simulations and SPEs for teaching and assessment, and barriers preventing use of these techniques. Design: Cross-sectional survey. Setting: Electronic survey. Patients or Other Participants: Forty-three professional program directors completed the survey, representing programs for doctoral, master's, and baccalaureate institutions. Data Collection and Analysis: The survey consisted of 8 demographic questions, 3 items regarding the frequency of using simulations and SPEs, 2 items regarding barriers to use, 1 item examining faculty collaborators and administrative release time, and 4 open-ended questions regarding additional uses and barriers. Cronbach [alpha] determined internal consistency, [alpha] = 0.891 to 0.911. Descriptive statistics were computed for all items. Results: Most respondents used simulations and SPEs for teaching and assessment. Simulation use occurred most in the curricular content areas of nonorthopaedic evaluation (n = 40, 97.6%), emergency care and life-threatening injuries (n = 38, 95.0%), and orthopaedic evaluation (n = 36, 87.8%). Regarding SPEs, use occurred most in the curricular content areas of orthopaedic evaluation (n = 32, 76.2%), nonorthopaedic evaluation (n = 32, 76.2%), and emergency care and life-threatening injuries (n = 28, 66.7%). Overall, a lack of faculty knowledge (4.40 ± 0.989), faculty time (4.36 ± 0.727), and financial resources for implementation (4.24 ± 1.100) were identified as barriers to use. Conclusions: Though simulations and standardized patients provide opportunities for engagement in real-time patient encounters in a safe learning environment, many educators still perceive a lack of evidence to support their use for teaching and assessment. Athletic training educators should seek mechanisms to increase the use of these techniques, as their use is important for preparing students for professional practice.

Effective collaboration and teamwork skills are critical in high-risk sectors, as deficiencies in these areas can result in injuries and risk of death. To foster the growth of these vital skills, immersive learning spaces have been created to simulate real-world scenarios, enabling students to safely improve their teamwork abilities. In such learning environments, multiple dialogue segments can occur concurrently as students independently organise themselves to tackle tasks in parallel across diverse spatial locations. This complex situation creates challenges for educators in assessing teamwork and for students in reflecting on their performance, especially considering the importance of effective communication in embodied teamwork. To address this, we propose an automated approach for generating teamwork analytics based on spatial and speech data. We illustrate this approach within a dynamic, immersive healthcare learning environment centred on embodied teamwork. Moreover, we evaluated whether the automated approach can produce transcriptions and epistemic networks of spatially distributed dialogue segments with a quality comparable to those generated manually for research objectives. This paper makes two key contributions: (1) it proposes an approach that integrates automated speech recognition and natural language processing techniques to automate the transcription and coding of team communication and generate analytics; and (2) it provides analyses of the errors in outputs generated by those techniques, offering insights for researchers and practitioners involved in the design of similar systems.

The increasing ubiquity of gamification in everyday life normalizes it as a motivational tool. While much scholarship supports gamification, labor sociologists have long problematized the phenomenon. In this mixed-methods action research study, we explore the results of gamifying a lesson on gamification in a sociology of work course. We designed two gamified activities with varying degrees of consent that followed a lesson on gamification and consent. Students rated how problematic a series of gamified work scenarios were before and after the intervention. Our quantitative data did not show a significant increase in students' ability to identify consent after the intervention, but we did discover that students took either an employee or employer's perspective in their rating justifications. Furthermore, these findings were gendered. This article highlights the need for a more critical take on gamification in the classroom. We conclude by suggesting ways practitioners can teach about gamification in other contexts.

Simulation is accepted as an effective method of learning procedural skills. However, the translational outcomes of skills acquired through simulation still warrants investigation. We designed this study to assess if skills laboratory training in addition to bedside learning (intervention group [IG]) would provide better learning results than bedside learning alone (control group [CG]) in the context of venipuncture training. This prospective, cluster-randomized, single-blind study took place at the Faculty of Medicine, University of Kelaniya, Sri Lanka. Seventeen clusters of second-year medical students were randomly assigned to either IG or CG. The IG trained on venipuncture in the skills laboratory, receiving instruction after modified Payton's Four Step Method. Following the training, students of both IG and CG underwent bedside learning for one month. Afterward, students of both groups performed venipuncture on actual patients in a clinical setting. An independent, blinded assessor scored students' performance using the Integrated Procedural Protocol Instrument (IPPI) and a checklist. Patients assessed students' performance with the Communication Assessment Tool (CAT). Eight and nine clusters were randomized to the intervention and control groups, respectively. IG completed significantly more single steps of the procedure correctly (IG: 19.36 ± 3.87 for checklist items; CG: 15.57 ± 4.95; p < 0.001). IG also scored significantly better on IPPI ratings (median: IG: 27 (12) vs. CG: 21 (8); p < 0.001). Rated by patients, students' communication skills did not significantly differ between the two groups. Simulation-based venipuncture training enabled students to perform the procedure on actual patients with a higher technical accuracy than students who learned venipuncture at the bedside. Students were able to transfer the skills acquired through venipuncture training at the skill laboratory to the bedside.

Biology is perhaps the most complex of the sciences, given the incredible variety of chemical species that are interconnected in spatial and temporal pathways that are daunting to understand. Their interconnections lead to emergent properties such as memory, consciousness, and recognition of self and non-self. To understand how these interconnected reactions lead to cellular life characterized by activation, inhibition, regulation, homeostasis, and adaptation, computational analyses and simulations are essential, a fact recognized by the biological communities. At the same time, students struggle to understand and apply binding and kinetic analyses for the simplest reactions such as the irreversible first-order conversion of a single reactant to a product. This likely results from cognitive difficulties in combining structural, chemical, mathematical, and textual descriptions of binding and catalytic reactions. To help students better understand dynamic reactions and their analyses, we have introduced two kinds of interactive graphs and simulations into the online educational resource, Fundamentals of Biochemistry, a LibreText biochemistry book. One is available for simple binding and kinetic reactions. The other displays progress curves (concentrations vs. time) for simple reactions and complex metabolic and signal transduction pathways. Users can move sliders to change dissociation and kinetic constants as well as initial concentrations and see instantaneous changes in the graphs. They can also export data into a spreadsheet for further processing, such as producing derivative Lineweaver-Burk and traditional Michaelis-Menten graphs of initial velocity (v[subscript 0]) versus substrate concentration.

Population-adjusted indirect comparison (PAIC) is an increasingly used technique for estimating the comparative effectiveness of different treatments for the health technology assessments when head-to-head trials are unavailable. Three commonly used PAIC methods include matching-adjusted indirect comparison (MAIC), simulated treatment comparison (STC), and multilevel network meta-regression (ML-NMR). MAIC enables researchers to achieve balanced covariate distribution across two independent trials when individual participant data are only available in one trial. In this article, we provide a comprehensive review of the MAIC methods, including their theoretical derivation, implicit assumptions, and connection to calibration estimation in survey sampling. We discuss the nuances between anchored and unanchored MAIC, as well as their required assumptions. Furthermore, we implement various MAIC methods in a user-friendly R Shiny application Shiny-MAIC. To our knowledge, it is the first Shiny application that implements various MAIC methods. The Shiny-MAIC application offers choice between anchored or unanchored MAIC, choice among different types of covariates and outcomes, and two variance estimators including bootstrap and robust standard errors. An example with simulated data is provided to demonstrate the utility of the Shiny-MAIC application, enabling a user-friendly approach conducting MAIC for healthcare decision-making. The Shiny-MAIC is freely available through the link: https://ziren.shinyapps.io/Shiny_MAIC/.

Population-adjusted indirect comparisons, developed in the 2010s, enable comparisons between two treatments in different studies by balancing patient characteristics in the case where individual patient-level data (IPD) are available for only one study. Health technology assessment (HTA) bodies increasingly rely on these methods to inform funding decisions, typically using unanchored indirect comparisons (i.e., without a common comparator), due to the need to evaluate comparative efficacy and safety for single-arm trials. Unanchored matching-adjusted indirect comparison (MAIC) and unanchored simulated treatment comparison (STC) are currently the only two approaches available for population-adjusted indirect comparisons based on single-arm trials. However, there is a notable underutilisation of unanchored STC in HTA, largely due to a lack of understanding of its implementation. We therefore develop a novel way to implement unanchored STC by incorporating standardisation/marginalisation and the NORmal To Anything (NORTA) algorithm for sampling covariates. This methodology aims to derive a suitable marginal treatment effect without aggregation bias for HTA evaluations. We use a non-parametric bootstrap and propose separately calculating the standard error for the IPD study and the comparator study to ensure the appropriate quantification of the uncertainty associated with the estimated treatment effect. The performance of our proposed unanchored STC approach is evaluated through a comprehensive simulation study focused on binary outcomes. Our findings demonstrate that the proposed approach is asymptotically unbiased. We argue that unanchored STC should be considered when conducting unanchored indirect comparisons with single-arm studies, presenting a robust approach for HTA decision-making.

The "LFK" index has been promoted as an improved method to detect bias in meta-analysis. Putatively, its performance does not depend on the number of studies in the meta-analysis. We conducted a simulation study, comparing the "LFK" index test to three standard tests for funnel plot asymmetry in settings with smaller or larger group sample sizes. In general, false positive rates of the "LFK" index test markedly depended on the number and size of studies as well as the between-study heterogeneity with values between 0% and almost 30%. Egger's test adhered well to the pre-specified significance level of 5% under homogeneity, but was too liberal (smaller groups) or conservative (larger groups) under heterogeneity. The rank test was too conservative for most simulation scenarios. The Thompson-Sharp test was too conservative under homogeneity, but adhered well to the significance level in case of heterogeneity. The true positive rate of the "LFK" index test was only larger compared with classic tests if the false positive rate was inflated. The power of classic tests was similar or larger than the "LFK" index test if the false positive rate of the "LFK" index test was used as significance level for the classic tests. Under ideal conditions, the false positive rate of the "LFK" index test markedly and unpredictably depends on the number and sample size of studies as well as the extent of between-study heterogeneity. The "LFK" index test in its current implementation should not be used to assess funnel plot asymmetry in meta-analysis.

Despite the growing interest in incorporating response time data into item response models, there has been a lack of research investigating how the effect of speed on the probability of a correct response varies across different groups (e.g., experimental conditions) for various items (i.e., differential response time item analysis). Furthermore, previous research has shown a complex relationship between response time and accuracy, necessitating a functional analysis to understand the patterns that manifest from this relationship. In this study, response time data are incorporated into an item response model for two purposes: (a) to examine how individuals' speed within an experimental condition affects their response accuracy on an item, and (b) to detect the differences in individuals' speed between conditions in the presence of within-condition effects. For these two purposes, by-variable smooth functions are employed to model differential and functional response time effects by experimental condition for each item. This model is illustrated using an empirical data set to describe the effect of individuals' speed on their reading comprehension ability in two experimental conditions of reading medium (paper vs. digital) by item. A simulation study showed that the recovery of parameters and by-variable smooth functions of response time was satisfactory, and that the type I error rate and power of the test for the by-variable smooth function of response time were acceptable in conditions similar to the empirical data set. In addition, the proposed method correctly identified the range of response time where between-condition differences in the effect of response time on the probability of a correct response were accurate.

Contribution: A novel proactive and collaborative learning paradigm was proposed to engage learners with different backgrounds and enable effective retention and transfer of the multidisciplinary artificial intelligence (AI)-cybersecurity knowledge. Specifically, the proposed learning paradigm contains: 1) an immersive learning environment to motivate the students for exploring AI/ machine learning (ML) development in the context of real-world cybersecurity scenarios by constructing learning models with tangible objects and 2) a proactive education paradigm designed with the use of collaborative learning activities based on game-based learning and social constructivism. Background: Increasing evidence shows that AI techniques can be manipulated, evaded, and misled, which can result in new and profound security implications. There is an education and training gap to foster a qualified cyber-workforce that understands the usefulness, limitations, and best practices of AI technologies in the cybersecurity domain. Efforts have been made to incorporate a comprehensive curriculum to meet the demand. There still remain essential challenges for effectively educating students on the interaction of AI and cybersecurity. Intended Outcomes: A novel proactive and collaborative learning paradigm is proposed to educate and train a qualified cyber-workforce in this new era where security breaches, privacy violations, and AI have become commonplace. Application Design: The development of this learning paradigm is grounded in the pedagogical approaches of technology-mediated learning and social constructivism. Findings: Although the research work is still ongoing, the prototype learning paradigm has shown encouraging results in promoting the learners' engagement in applied AI learning.

Most existing diagnostic models are developed to detect whether students have mastered a set of skills of interest, but few have focused on identifying what scientific misconceptions students possess. This article developed a general dual-purpose model for simultaneously estimating students' overall ability and the presence and absence of misconceptions. The expectation-maximization algorithm was developed to estimate the model parameters. A simulation study was conducted to evaluate to what extent the parameters can be accurately recovered under varied conditions. A set of real data in science education was also analyzed to examine the viability of the proposed model in practice.

Identifying items with differential item functioning (DIF) in an assessment is a crucial step for achieving equitable measurement. One critical issue that has not been fully addressed with existing studies is how DIF items can be detected when data are multilevel. In the present study, we introduced a Lord's Wald X[superscript 2] test-based procedure for detecting both uniform and non-uniform DIF with polytomous items in the presence of the ubiquitous multilevel data structure. The proposed approach is a multilevel extension of a two-stage procedure, which identifies anchor items in its first stage and formally evaluates candidate items in the second stage. We applied the Metropolis-Hastings Robbins-Monro (MH-RM) algorithm to estimate multilevel polytomous item response theory (IRT) models and to obtain accurate covariance matrices. To evaluate the performance of the proposed approach, we conducted a preliminary simulation study that considered various conditions to mimic real-world scenarios. The simulation results indicated that the proposed approach has great power for identifying DIF items and well controls the Type I error rate. Limitations and future research directions were also discussed.

Forced-choice (FC) measures have been widely used in many personality or attitude tests as an alternative to rating scales, which employ comparative rather than absolute judgments. Several response biases, such as social desirability, response styles, and acquiescence bias, can be reduced effectively. Another type of data linked with comparative judgments is response time (RT), which contains potential information concerning respondents' decision-making process. It would be challenging but exciting to combine RT into FC measures better to reveal respondents' behaviors or preferences in personality measurement. Given this situation, this study aims to propose a new item response theory (IRT) model that incorporates RT into FC measures to improve personality assessment. Simulation studies show that the proposed model can effectively improve the estimation accuracy of personality traits with the ancillary information contained in RT. Also, an application on a real data set reveals that the proposed model estimates similar but different parameter values compared with the conventional Thurstonian IRT model. The RT information can explain these differences.

Although parallel analysis has been found to be an accurate method for determining the number of factors in many conditions with complete data, its application under missing data is limited. The existing literature recommends that, after using an appropriate multiple imputation method, researchers either apply parallel analysis to every imputed data set and use the number of factors suggested by most of the data copies or average the correlation matrices across all data copies, followed by applying the parallel analysis to the average correlation matrix. Both approaches for pooling the results provide a single suggested number without reflecting the uncertainty introduced by missing values. The present study proposes the use of an alternative approach, which calculates the proportion of imputed data sets that result in k (k = 1, 2, 3 . . .) factors. This approach will inform applied researchers of the degree of uncertainty due to the missingness. Results from a simulation experiment show that the proposed method can more likely suggest the correct number of factors when missingness contributes to a large amount of uncertainty.

The forced-choice response format is often considered superior to the standard Likert-type format for controlling social desirability in personality inventories. We performed simulations and found that the trait information based on the two formats converges when the number of items is high and forced-choice items are mixed with regard to positively and negatively keyed items. Given that forced-choice items extract the same personality information as Likert-type items do, including socially desirable responding, other means are needed to counteract social desirability. We propose using evaluatively neutralized items in personality measurement, as they can counteract social desirability regardless of response format.