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The authors present a Web application they designed in the R programming language as an experiential learning tool for teaching production theory. The app simulates production decisions where a manager is tasked to find the optimal mixture of inputs through experimentation. Users of the application are instructed to use calculations and intuitions from production theory to improve profitability quickly. The underlying parameters and starting points are randomized to allow for additional practice. Variations of the exercise correspond to cost-minimization and profit-maximization problems with and without market power in the output market. Also, the app provides dynamic, interactive visualizations in 3D in order to assist in a better understanding of standard production theory graphs. The app is located at https://bit.ly/387HsHL.

Background: Higher education is expected to prepare students with interdisciplinary learning (IDL), which is important for their educational and working life opportunities. The cocreation of knowledge in interdisciplinary teams offers multiple opportunities for the emergence of collective knowledge objects (KOs) and knowledge practices (KPs). Methods: During iterations of an organization simulation course, interdisciplinary student teams created an offer of human resource services for a client. To analyze the students' IDL (84 students in 12 teams), we conducted an interaction analysis, drawing on sociocultural and knowledge practice perspectives on technology-mediated learning. First, video-recordings of two teams' meetings were analyzed to trace the tensions, negotiations, and cocreation of KOs. Second, students' reflective diaries were analyzed to identify collective KPs. Findings: The negotiation and cocreation of KOs were mediated by multiple material resources and participants' disciplinary knowledge. In their diaries, students described the following collective KPs: 1) attending to interdisciplinary problems, 2) responsibility taking, 3) framing expertise and contribution, 4) crossing interdisciplinary boundaries, 5) exploring and concretizing new knowledge, and 6) reflecting and expanding upon practices and knowledge. Contributions: The study widens our understanding of the intertwined dynamics of KOs and KPs through which students collectively create and engage in interdisciplinary learning.

Consultation evenings, also known as parent-teacher conferences, are important opportunities for teachers to strengthen their relationships with caregivers. Many teachers, however, are unprepared, having had few opportunities to build skills and participate in real consultations during teacher training. To provide student teachers with more practice opportunities, some teacher educators have begun supplementing students teachers' real-world consultations with simulations. Our goal in this study was to use findings on students' strengths and challenges in a simulated consultation to inform the design of future practice opportunities. Using factor analysis and descriptive statistics, we analysed 206 transcripts from 106 student teachers' simulations to uncover patterns in their consultations. We found that students were consistently good at sharing positive information about the pupil. Student teachers had more challenges finding the balance between facilitating a productive meeting and a collaborative one. Students also varied in how well they created and maintained a welcoming meeting environment when challenged by the caregiver or presented with a personal disclosure. Based on these findings, we propose designing targeted approximations of practice for consultations, in addition to more holistic ones, so that students can build skills in areas such as finding the balance between productivity and collaboration in a meeting.

Mediation analysis is widely applied in various fields of science, such as psychology, epidemiology, and sociology. In practice, many psychological and behavioral phenomena are dynamic, and the corresponding mediation effects are expected to change over time. However, most existing mediation methods assume a static mediation effect over time, which overlooks the dynamic nature of mediation effect. To address this issue, we propose dynamic mediation models that can capture the dynamic nature of the mediation effect. Specifically, we model the path parameters of mediation models as auto-regressive (AR) processes of time that can vary over time. Additionally, we define the mediation effect under the potential outcome framework, and examine its identification and causal interpretation. Bayesian methods utilizing Gibbs sampling are adopted to estimate unknown parameters in the proposed dynamic mediation models. We further evaluate our proposed models and methods through extensive simulations and illustrate their application through a real data application.

In this study, different degrees of synchronous and asynchronous online social interactions are investigated in the context of an online educational roleplaying simulation game that is played across multiple classrooms simultaneously to teach argumentation skills and social studies. Results from 45 K-12 middle school social studies teachers and 867 students over 3 study conditions were compared based on the degree of real-time discussion that was embedded in each condition's version of game (i.e., two scheduled live conferences, one scheduled live conference, and asynchronous-only interactions or zero live conferences). All conditions exhibited significant small to moderate-level pre-post effect sizes, including the condition featuring asynchronous-only discussions. Additionally, the "mid-range" 1 live conference condition exhibited the greatest pre-post effect size in comparison to the other two conditions. This study demonstrates evidence for the benefits of implementing asynchronous-only discussions in digital interventions in comparison to live discussions when synchronous interaction may not be feasible. For designers, implementing both asynchronous and synchronous interactions based on available resources and feasibility can be used to maximize social presence among participants in educational roleplaying games and other virtual learning environments.

Due to the COVID-19 pandemic, lecturers of higher learning institutions had to pivot quickly from face-to-face classes to online classes. The new normal of online teaching and learning challenged lecturers in keeping their students engaged, especially when teaching a language course that heavily focuses on the writing component. The purpose of this study was to examine students' perception of using Padlet as a learning space to simulate real-life business communication. At the end of a 14-week semester language course, a cohort of 38 diploma students responded to a self-administered online survey with a 79% response rate. Findings from the descriptive analysis indicated high mean values for most survey items measured, implying that the students were generally favourable towards the use of Padlet and the simulation approach in learning business communication. Curriculum designers and lecturers of other courses could consider the potential of using Padlet as a learning space for simulation. Recommendations, limitations, and future research directions are also discussed in this paper.

The purpose of this study was to determine if participation in the Community Action Poverty Simulation (CAPS) had an impact on rural educator candidates' and practicing rural educators' attitudes toward poverty (ATP). The group of rural educator candidates are students pursuing an undergraduate degree in education at a small, rural university in Alabama. Practicing educators who participated in the research were from a rural school in west Alabama. The CAPS is a one-hour simulation made up of four 15-minute weeks. Each 15-minute time segment simulates one week in poverty. In each week, participants have various tasks to complete in the allotted time. Participants in the simulation take on the roles of individuals living in poverty. Data was examined from two different simulation groups, rural educator candidates and practicing rural educators. All participants completed a demographic information sheet and the Pretest before participation in the CAPS. Following the simulation, all participants are involved in the debrief session. This session, led by the facilitator, allows participants to discuss the range of feelings they experienced during the simulation. After the debrief portion of the simulation, participants completed the Posttest. Statistical analysis using SPSS was conducted. Data were analyzed using a paired samples t-test. The results indicated an increased (more positive) ATP score (M[subscript 1] = 3.65, M[subscript 2] = 3.68) for rural educator candidates, but there was not a statistically significant difference (p=0.578). However, the data for practicing rural educators indicated an increase in the ATP score (M[subscript 1] = 3.51, M[subscript 2] = 3.68) and a statistically significant difference (p=0.000). Based on the data analysis, it was concluded that participation in the CAPS has a greater impact on practicing educators versus undergraduate education majors. Rural school leaders grapple with ways to ensure students living in poverty have the same learning opportunities as other students to thrive academically. Often school accountability is focused on high-stakes testing results. Across the nation, there is an increase of children from homes of poverty, who have unique educational needs. Rural schools are faced with barriers such as funding, isolation, and community support. School leaders must ensure faculty and staff have a clear understanding of poverty and how poverty can affect a student's educational journey; hence, the need to provide poverty simulation training.

This article both describes and explains the nature of system simulations--the generation of (non-)numeric models representing characteristics, behaviors, or functions of physical or abstract systems/processes under study. For ease of presentation, I first present some of the most pressing theoretical-practical considerations concerning implications for the gamification of education in general and foreign/second language education in particular. Structural, cognitive, and content affordances of gamified learning are reviewed next, and the relevant knowledge, skills, and dispositions related to the purposeful design and development of digital gaming and game-like activities for classroom or personal use are noted as needed, including the learning behaviors deemed critical in second language acquisition. Thereafter, I discuss how such behaviors are discerned and actualized in the entertainment/education software collectively named system simulations, the pedagogical benefits attained through their judicious use, and the key features of some notable reacting games, (real-time and turn-based) strategy games, simulation "sandbox-style" games, and, finally, single-player simulation computer/video games. I conclude the article with a brief summary of propositions deemed best to harness the power of gaming in foreign and second language education. Evolution, curiosity, and discovery are but three closing constructs I ask readers to heed in the months and in the years ahead.

There is a current 'theory crisis' in language acquisition research, resulting from fragmentation both at the level of the approaches and the linguistic level studied. We identify a need for integrative approaches that go beyond these limitations, and propose to analyse the strengths and weaknesses of current theoretical approaches of language acquisition. In particular, we advocate that language learning simulations, if they integrate realistic input and multiple levels of language, have the potential to contribute significantly to our understanding of language acquisition. We then review recent results obtained through such language learning simulations. Finally, we propose some guidelines for the community to build better simulations.

Electronic cigarettes are the most widely used tobacco product among youth in the United States. Although rapidly growing, research on effective message strategies for e-cigarette use prevention is still limited. This study examined the relative effectiveness of gain framing versus loss framing in youth-targeting prevention text messages delivered either as individual expository texts or simulated text exchanges between a youth patient and a pediatrician. A national sample of 1,084 youth susceptible to future e-cigarette use was randomized to condition in an online message testing experiment featuring a 2 (framing: gain vs. loss) × 2 (format: individual texts vs. simulated exchange) factorial design. Results revealed a consistent interaction between framing and messaging format in message liking, positive affect, attitude toward e-cigarette use, and future e-cigarette use intentions. The gain frame outperformed the loss frame in the simulated exchange conditions while the reverse trend was true for the individual text conditions. Furthermore, the main effect of messaging format was significant on multiple outcomes in favor of simulated text exchanges. The main effect of framing was only significant on negative affective response with the loss frame eliciting stronger responses. These findings suggest that the relative effectiveness of gain framing versus loss framing depends on how messages are presented in youth-targeting text messaging interventions. When messages are likely to be delivered in a discrete manner, the loss frame should be preferred. When greater interactivity and narrative development are possible, the gain frame should be favored. E-cigarette prevention efforts should leverage these insights to enhance message effectiveness.

Any time examinees have had access to items and/or answers prior to taking a test, the fairness of the test and validity of test score interpretations are threatened. Therefore, there is a high demand for procedures to detect both compromised items (CI) and examinees with preknowledge (EWP). In this article, we develop a procedure that uses item scores and distractors to simultaneously detect CI and EWP. The false positive rate and true positive rate are evaluated for both items and examinees using detailed simulations. A real data example is also provided using data from an information technology certification exam.

This study explored the feasibility of using knowledge surveys in a pre-licensure professional nursing program using cognitive and behavioral outcomes. This study illustrates the incorporation of profession-specific competencies. It introduces the KS as a potentially valuable educational tool for a blended learning approach in higher education programs that include simulation learning.

We discuss analysis of 5-grade Likert type data in the two-sample case. Analysis using two-sample "t" tests, nonparametric Wilcoxon tests, and ordinal regression methods, are compared using simulated data based on an ordinal regression paradigm. One thousand pairs of samples of size "n"=10 and "n"=30 were generated, with three different degrees of skewness. For all sample sizes and degrees of skewness, the ordinal probit model has highest power. This is not surprising since the data was generated with this model in mind. Slightly more surprising is that the "t" test has higher power than the Wilcoxon test in all studied situations, even for skewed data. For "n"=30, the differences between the methods are small.

The study aims to reveal the effect of simulation-based experiential learning applications on gaining problem-solving skills in the Social Studies curriculum. The research was carried out in an experimental model, and the data were obtained according to the controlled pre-test and post-test approach. Social process simulation, as a type of social simulation, was preferred during the application process. Three new and originally developed social process simulations were used in the context of the simulation-based experiential learning applications for the learning theme of "Power, Management and Society" in the 7th grade social studies curriculum. According to the time prescribed in the program, the course implementation continued for 4 weeks (12 lessons) in total. The research was carried out in Usak's Karahalli District Cumhuriyet Secondary School. The research study group composed of 42 students; 21 students in the experimental group and 21 students in the control group participated in the research. The "Problem Solving Skills Scale" consisting of 4 dimensions was used as the research data collection tool. Mann Whitney U Test and Wilcoxon Signed Ranks Test as non-parametric tests were used to analyze the data obtained in the study. According to research results, the post-test results of the experimental group students who were educated in the simulation-based experiential learning model were significantly higher than the control group students who were educated with the methods prescribed in the programme. In conclusion, in this context, it has been reached that simulation-based experiential learning applications enhance students' problem-solving skills.

Item parameter drift (IPD) is the systematic differentiation of parameter values of items over time due to various reasons. If it occurs in computer adaptive tests (CAT), it causes errors in the estimation of item and ability parameters. Identification of the underlying conditions of this situation in CAT is important for estimating item and ability parameters with minimum error. This study examines the measurement precision of IPD and its impacts on the test information function (TIF) in CAT administrations. This simulation study compares sample size (1000, 5000), IPD size (0.00 logit, 0.50 logit, 0.75 logit, 1.00 logit), percentage of items containing IPD (0%, 5%, 10%, 20%), three time points and item bank size (200, 500, 1000) conditions. To examine the impacts of the conditions on ability estimations; measurement precision, and TIF values were calculated, and factorial analysis of variance (ANOVA) for independent samples was carried out to examine whether there were any differences between estimations in terms of these factors. The study found that an increase in the number of measurements using item bank with IPD items results in a decrease in measurement precision and the amount of information the test provides. Factorial ANOVA for independent samples revealed that measurements precision and TIF differences are mostly statistically significant. Although all IPD conditions negatively affect measurement precision and TIF, it has been shown that sample size and item bank size generally do not have an increasing or decreasing effect on these factors.

This study is intended to explore an applicable and effective model of simulated situation for English as a Foreign Language (EFL) learners and also investigate the effects of the simulated environment on Willingness to Communicate (WTC) of the learners. To carry out this study, 300 elementary level EFL learners were chosen. A Key English Test (KET) was administered to ensure homogeneity on the learners. They were divided into two groups of experimental and control. A WTC questionnaire developed by Macintyre, Baker, Clement, and Conrod (2001) was used, after validation through Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) and Modeling, as an instrument to obtain primary data. The results of Mann-Whitney U test revealed that simulated environment had positive effects on the participants' WTC. The findings of this study suggest that understanding how a simulated environment affects EFL learners' success in speaking proficiency can help institutes to provide such environments for EFL learners and instructors. This method can be presented at different levels of English proficiency. The focus of this study was mainly on speaking skill; therefore, similar studies can be conducted regarding other language skills, e.g., writing, listening and reading.

This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent classes (2, 3); missing data type (complete, missing at random (MAR) and missing not at random (MNAR)), and the percentage of missing data (10%, 20%). Data were generated for each of the three mixture IRT models using the code written in R program. "MplusAutomation" package, which provides the automation of R and Mplus program, was used to analyze the data. The mean RMSE values for item difficulty, item discrimination, and guessing parameter estimation were determined. The mean RMSE values as to the Mixture Rasch model were found to be lower than those of the Mixture 2PL and Mixture 3PL models. Percentages of classification accuracy were also computed. It was noted that the Mixture Rasch model with 30 items, 2 classes, 1000 sample size, and complete data conditions had the highest classification accuracy percentage. Additionally, a factorial ANOVA was used to evaluate each factor's main effects and interaction effects.

Drug and alcohol neonate simulators were used to highlight the effects of substance misuse on prenatal development within lifespan development modules to 61 Psychology undergraduates and 12 sixth-form Health and Social Care students. A mixed method approach was used considering both knowledge development and perceptions of experiential hands-on learning. Student knowledge of the effects of drugs and alcohol on prenatal development was assessed before and after an interactive session on teratogenesis utilising neonate simulators demonstrating these effects. With this experiential learning approach, the statistical analysis combining both groups showed increased knowledge after the interactive session, and the students perceived this enhanced understanding to be a direct result of hands-on interaction with the neonate simulators. The researchers encourage the use of neonate simulators as good practice that can be effectively incorporated into the psychology and other health-related teaching contexts to facilitate knowledge on teratogenesis.

This paper presents an application of the Kalman filter in signal processing in instrumentation systems when the conditions of the environment generate a large amount of interference for the acquisition of signals from measurement systems. The unwanted interferences make important use of the instrumentation system resources and do not represent useful information under any aspect. A simulation is presented using the Matlab tool, which remarkably facilitates the information processing so that the corresponding actions are taken according to the information obtained, taking advantage of the current resources offered by the embedded systems and the required measurements are obtained with enough accuracy.

This article shows results on the simulation of partial differential equations such as the heat equation, the Laplace equation and the wave equation in a course called mathematical methods at a university in Bogotá Colombia. In this course, the concept of partial differential equations and different solution methods were explained to them, both in the analytical and numerical part, the importance they have in the physical sciences, the exact sciences and many of their different applications in engineering, since students. They are in the fifth semester of the mechatronic engineering degree, then under the methodology of didactic situations they were presented with a particular situation where by developing code in the mathematics and electronic simulation software called Matlab, some of these could be simulated, giving different values to constants and describing their behavior just as it was possible to visualize some results of the main partial differential equations, with quite significant results.

This study aims to compare normality tests in different sample sizes in data with normal distribution under different kurtosis and skewness coefficients obtained simulatively. To this end, firstly, simulative data were produced using the MATLAB program for different skewness/kurtosis coefficients and different sample sizes. The normality analysis of each data type was conducted using the MATLAB program and ten different normality tests; namely, (Kolmogorov Smirnov (KS) Test, KS Stephens Modification, KS Marsaglia, KS Lilliefors Modification, Anderson-Darling Test, Cramer-Von Mises Test, Shapiro-Wilk Test, Shapiro-Francia Test, Jarque-Bera Test, and D'Agostino & Pearson Test). As a result of the analyses conducted according to ten different normality tests, it was found that normality tests were not affected by the sample size when the skewness and kurtosis coefficients were equal to or close to zero; however, in cases where the skewness and kurtosis coefficients moved away from zero, it was found that normality tests are affected by the sample size, and such tests tend to give significant results. Therefore, in large samples, it may be suggested that critical values for skewness and kurtosis coefficients' z-scores as proposed by Kim (2013) and Mayers (2013) or the histogram graphs be used.

The purpose of this study was to investigate the Type I Error findings and power rates of the methods used to determine dimensionality in unidimensional and bidimensional psychological constructs for various conditions (characteristic of the distribution, sample size, length of the test, and interdimensional correlation) and to examine the joint effect of the conditions (effect of the interaction of conditions) as well as the main effect of each condition. The simulative data were generated for the study using the SAS program. Within the scope of the study, the data were analyzed using the DIMTEST T statistic and the Dimensionality DETECT IDN index, which is one of the non-parametric methods. The Nonlinear Factor Analysis (NOHARM) method was preferred from among parametric methods. As a result of the study, it was noted that the most consistent results in making the unidimensionality decisions belong to the Nonlinear Factor Analysis method showing standard normal distribution according to the shape of the distribution. When the power study results were examined, it was noted that the DIMTEST T statistic gave more accurate results in conditions with large samples, consisting of data with standard normal distribution. On the other hand, while results of the DETECT IDN index and Nonlinear factor analysis were more internally consistent, it was noted that in conditions where the sample size was 1000 and above, the DIMTEST T statistic also made the right decisions in determining dimensionality.

This study aimed to 1) investigate the results of remote learning combined with competency-based classroom simulation activities, including academic achievement, the ability to teach online, and learning satisfaction, and 2) compare among the self-assessment, the lecturer's assessment, and the classmates' assessment of the pre-service computer teachers' online teaching ability. The samples consisted of 18 fourth-year students who were chosen by using a cluster random sampling lottery method. A unit is a group of classes. The statistics employed in the research were mean, standard deviation, t-test (Dependent Samples), and F-test (Oneway ANOVA). The findings were reported that students had post-test scores higher than pretest scores at the level of 0.05. The self-assessment, lecturer's assessment, and the classmates' assessment of the pre-service computer teachers' online teaching ability were at the highest level. The students' satisfaction with remote learning combined with competency-based classroom simulation activities teaching online by pre-service computer teachers was at the highest level, and in the overall aspect, the comparative results of the pre-service computer teachers' self-assessment, the lecturer's assessment, and the classmates' assessment were not different.

Response process data have the potential to provide a rich description of test-takers' thinking processes. However, retrieving insights from these data presents a challenge for educational assessments and educational data mining as they are complex and not well annotated. The present study addresses this challenge by developing a computational model that simulates how different problem-solving strategies would behave while searching for a solution to a Program for International Student Assessment (PISA) 2012 problem-solving item, and uses n-gram processing of data together with a naïve Bayesian classifier to infer latent problem-solving strategies from the test-takers' response process data. The retrieval of simulated strategies improved with increased n-gram length, reaching an accuracy of 0.72 on the original PISA task. Applying the model to generalized versions of the task showed that classification accuracy increased with problem size and the mean number of actions, reaching a classification accuracy of 0.90 for certain task versions. The strategy that was most efficient and effective in the PISA Traffic task evaluated paths based on the labeled travel time. However, in generalized versions of the task, a straight line strategy was more effective. When applying the classifier to empirical data, most test-takers were classified as using a random path strategy (46%). Test-takers classified as using the travel time strategy had the highest probability of solving the task. The test-takers classified as using the random actions strategy had the lowest probability of solving the task. The effect of (classified) strategy on general PISA problem-solving performance was overall weak, except for a negative effect for the random actions strategy ([beta] [approximately equal to] -65, CI[subscript 95%] [approximately equal to] [-96, -36]). The study contributes with a novel approach to inferring latent problem-solving strategies from action sequences. The study also illustrates how simulations can provide valuable information about item design by exploring how changing item properties could affect the accuracy of inferences about unobserved problem-solving strategies.

In the last decades, the development of computerized adaptive testing (CAT) has allowed more precise measurements with a smaller number of items. In this study, we develop an item bank (IB) to generate the adaptive algorithm and simulate the functioning of CAT to assess the domains of mathematical knowledge in Argentinian university students (N=773). Data were analyzed from the Rasch model. A simulation design created with the R software was used to determine the necessary items of the IB to estimate examinee ability. Our results indicate that the IB in the domains of mathematical knowledge is adequate to be applied in CAT, especially to estimate average ability levels. The use of CAT is recommended for rapidly generating indicators of the knowledge acquired by students and to design educational strategies that enhance student performance. Results, constrains, and implications of this study are discussed.

Computational and atmospheric chemistry are two important branches of contemporary chemistry. With the present topical nature of climate change and global warming, it is more crucial than ever that students are aware of and exposed to atmospheric chemistry, with an emphasis on how modeling may aid in understanding how atmospherically relevant chemical compounds interact with incoming solar radiation. Nonetheless, computational and atmospheric chemistry are under-represented in most undergraduate chemistry curricula. In this manuscript, we describe a simple and efficient method for simulating the electronic absorption spectral profiles of atmospherically relevant molecules that may be utilized in an undergraduate computer laboratory. The laboratory results give students hands-on experience in computational and atmospheric chemistry, as well as electronic absorption spectroscopy.

Situational simulation teaching method (SST mentioned below) is a mature teaching method that has been applied. It has been widely used in foreign language, law, management, clinical and other fields, and has been proved to have good teaching effect. The quality of teachers is the key to improve the international competitiveness of China's education system. With the growth of China's population and the reform and development of education, the training of pre-service teachers has become a public concern. According to the existing research, most of the pre-service teachers have good academic and moral qualities, but there are still deficiencies in teaching ability, management ability and communication ability. In view of this phenomenon, this paper puts forward a scheme of training chemistry pre-service teachers by using SST method through the way of organic chemistry teaching reform. The results show that SST method can improve students' learning quality and cultivate students' comprehensive abilities (including pre-service teachers' professional skills).

The use of a Practice set (case simulation) as an assessment task in management accounting is aimed at providing students with a practical experience in the application of a form of simulated real-world events. The pedagogical justification for the use of a case simulation is inherent in the concept referred to as "learn-by-doing" effectively this implies that students are more likely to gain a deeper understanding of the knowledge and skills involved by having to complete a specific task.

Clinical education standards for speech-language pathology and nursing programs indicate the need for students to gain experience with interprofessional collaborative practice (ICP). However, colleges not affiliated with hospitals struggle to offer experiences between healthcare disciplines. The purpose of this paper is to present a case study as a model for interprofessional healthcare simulation that can be applied to schools that have limited access to a variety of professional programs and few complimentary medical specialties at their home institution. The partnership of a masters in speech-language pathology (MS-SLP) program at a public state sponsored institution and a bachelors of science in nursing (BSN) program at a private college provides insights on model effectiveness. A strong partnership between simulation facilitators allowed for agreement on learning objectives, mapping the experience from pre-brief to debrief, and maintenance of unique professional roles for greater authenticity. MS-SLP and BSN students reported high ratings of confidence, understanding of other professional roles, and a shared respect for the unique roles and responsibilities of each team member. Strengths and challenges of the approach are discussed.

Financial professionals involved in divorce proceedings, whether for a client or an attorney, often use software to project the ability of a dependent spouse to earn income off of her separate estate. These projections have historically relied on static inputs and use a Monte Carlo simulation to illustrate the paths a portfolio might take. Within this study, the effects on dynamic income and expense changes on outcomes were examined. A comparison was made between the traditional Monte Carlo methods and Markov Chain Monte Carlo (MCMC) methods. Results using MCMC methods more closely approximated investment return distribution, and illustrated investable assets were the primary driver of long-term success, and not items such as spousal or child support. Practical implications for financial professionals, family law attorneys, judges, and clients are discussed as well as opportunities for future research.

This study examined concerns that teacher candidates have about communicating with families and studied the use of three simulation techniques to enhance candidates' confidence and perception of preparedness for communicating with diverse families. Twenty-five teacher candidates in a senior-level education class participated in three simulation conditions: Peer-to-Peer role playing, parent actors, and technology-based simulation using avatars in TeachLivE™. Data were collected using surveys before, during, and after the simulation sessions. A t-test revealed that candidates felt more confident in their abilities after the simulations, and inspection of means revealed that the parent actors were found to be the most preferred simulation condition. Inductive analysis was used to establish themes in the qualitative responses, showing that candidates were most concerned about appearing confident and discussing difficult topics. Based on the findings, the authors recommend the inclusion of structured simulations involving parent and teacher interactions during teacher preparation programs.

The purpose of this study was to find out the influence of the integration sequence of interactive simulation on the construction of the scientific explanation of buffer solutions. This study was conducted with 30 pre-service science teachers. The control group was randomly assigned to study with lecture first and then interactive simulation-based inquiry learning, and the experimental group was randomly assigned to study with interactive simulation-based inquiry learning and lecture respectively. The finding showed that after the posttest there was no statistically significant difference between the control and experimental groups. This suggests that the sequence of interactive simulation during inquiry activities in the chemistry classroom does not affect the construction of the scientific explanation. However, the mean score between the pretest and posttest in the control group shows a statistically significant difference. This study yields productive information regarding the role of interactive simulation providing clear evidence to scaffold pre-service science teachers in learning the abstract concept.

Teaching physical science has been challenging for educators for quite some time, and with the COVID-19 pandemic, the situation has even worsened which made the adoption of blended learning in the different cycles of education only a matter of time. This paradigm requires nevertheless a certain command when it comes to using some specific tools dedicated to the simulation of some physical science knowledge laboratories. The objective of this research is to study the effect of integrating the "Simulation Program with Integrated Circuit Emphasis" simulator tool in a blended learning environment on the conceptual learning of electricity. To achieve this goal, we adopted a quantitative methodology to assess the outcome of the experience which involved 40 pupils. The experimental group teacher used blended learning and integrated the simulation to teach the electricity module. The same teacher adopted traditional teaching with the control group (40 pupils). The instrument used is a test instrument in the form of a quiz which consists of 20 questions. All questions were in the form of multiple-choice questions to facilitate a more efficient analysis. The results of this research report the positive effects of integrating simulation into a blended learning environment with a statistically significant difference. Moreover, the experiment shows that 90 per cent of the pupils in the experimental group passed the test, as opposed to 75 per cent of the control group.

Solving real-life problems through mathematical modeling is one of the aims of modern mathematics curricula. For this reason, prospective mathematics teachers need to acquire modeling skills and use these skills in learning environments in terms of creating rich learning environments. With this study, it is aimed to examine the reflections of using a simulation on a problem involving uncertainty on the probabilistic thinking of prospective teachers. The activity includes an experimental review of the famous Hat problem. It was observed that the hat problem, which started as a puzzle, was linked to coding theory and reached the limit of mathematics, statistics, and computer science research. Research findings revealed that the simulation-supported learning environment not only contributes to prospective teachers' probabilistic thinking skills, but also offers the opportunity to experience different methods (such as working with real data, technology assisted learning, modeling) in teaching and learning mathematics. It has been concluded that simulations have a unique potential that other methods do not have in terms of gaining statistical thinking as well as problem solving and modeling skills.

In response to the paucity of clinical placements available in 2020 due to the COVID-19 pandemic, alternate options for prelicensure students were necessary in order for them to complete the fieldwork required for graduation. In response, Curtin University replaced a faculty-led fully-simulated placement with a peer-assisted learning model. This incorporated final-year students acting as peer teachers to penultimate-year students, thus creating new learning and teaching placements for the final-year students. To our knowledge, this had never been done on such a scale before. Considering the importance of meeting learner expectations in the tertiary setting, the perceptions of peer learners around the innovation were important but unknown. This study used a prospective qualitative observational design that utilized feedback from peer learners relating to learning using the peer-assisted model. Peer learners provided written reflections that were analysed thematically. During November and December 2020, 171 penultimate-year physiotherapy students participated in one of two three-week placements, and 170 consented to participate in data collection. Qualitative data reflected several enablers and barriers to learning during the experience. These related to the peer teacher attributes, the provision of performance feedback, the learning environment, and the facilitation of clinical reasoning. Peer learners enjoyed the peer-assisted model, found peer teachers able to facilitate learning, and provided useful insights that will shape future placements. The success of the model supports repeating it in the future. This will maintain a bilateral exchange of peer-led clinical learning and teaching with diminished faculty supervisory workload.

This research aims to analyse students' conceptual understanding of chemical equilibrium matter using Physics Education Technology (PhET) Interactive Simulations. Students' misconceptions can be caused by the difficulty in connecting the sub-microscopic, macroscopic, and symbolic levels of understanding in chemistry. The study was conducted at a secondary school with a total sample of 108 students using a quantitative research method. The results showed that multiple-choice questions of the two-tier Chemical Equilibrium Diagnostic Instrument (CEDI) used in this study meet with the Rasch measurement model. The students who answered correctly on content knowledge ranged from 11.1-90.7%. However, the percentage decreased to 11.1-84.3% once the content knowledge and reasons were combined. The option probability curve responses identified the students' misconceptions that were further investigated by interviews. PhET Interactive Simulations require improvements or additional features to help students better understand conceptual understanding through analogies of product and reactant molecules' movement in the equilibrium system.

Preparing students for the workforce is a balancing act that involves theory, practice, and assessment. As students navigate an educational experience that is, however, often distant from real-world needs, it is imperative that academia finds a novel way to bridge the gap. As many organizations utilize open challenges to attract ideas and talent, academia can easily create such bridge, leading to greater engagement, greater student preparation, and a potential employment pipeline. This paper describes the experience of our students and faculty advisors who participated to the NASA SUITS (Spacesuit User Interface Technologies for Students) Design Challenge. In particular, we review the pedagogical value of the solution that they created and the changes that were implemented in the curriculum of an undergraduate degree program in Information Technology. This open-source, multi-year project is also a flexible platform that can be utilized for engagement in K-12 education as well as graduate research projects.

We study the automatic identification of educational items worthy of content authors' attention. Based on the results of such analysis, content authors can revise and improve the content of learning environments. We provide an overview of item properties relevant to this task, including difficulty and complexity measures, item discrimination, and various forms of content representation. We analyze the potential usefulness of these properties using both simulation and analysis of real data from a large-scale learning environment. We also describe two case studies where we practically apply the identification of attention-worthy items. Based on the analysis and case studies, we provide recommendations for practice and impulses for further research.

All cognitive diagnostic models that evaluate educational test data require a Q-matrix that combines every item in a test with the required cognitive skills for each item to be answered correctly. Generally, the Q-matrix is constructed by education experts' judgment, leading to some uncertainty in its elements. Various statistical methods are suggested to validate misspecifications in the Q-matrix. This paper evaluates the performance of the Q-matrix validation methods, the sequential expectation-maximization-based [delta]-method (SEM [delta]-method), and the Q-matrix refinement (QMR) method using a study with real data and simulations. The simulation design results showed that the misspecification percentage and the length of the test had a small or no effect on the mean q-entry recovery rates (MRRs) of both methods, while the increase in sample size had an improving effect. The MRRs of both methods decreased when the number of attributes and guessing (g) - slip (s) parameters increased. According to simulation study results, the QMR method performed better than the SEM [delta]-method. For the q-matrix validation, it can be suggested that CDM practitioners prioritize the QMR method and use a sample size of 1,000. On the other hand, the real data results revealed that the MRRs of both methods were at the base rates. This result highlights the need for further research on method comparison, specifically for real-world data applications where the number of attributes is relatively large and the test duration is short.