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Purpose: To explore perceptions of student learning in undergraduate nursing students who repeat the fundamentals nursing course and simultaneously take a support course. Methods: This qualitative descriptive design was conducted at one private liberal arts college. The study included interviews with six undergraduate baccalaureate nursing students repeating the fundamentals course and their perceptions following the repeated course. Results: Themes of discovering the value of repeating a course, attending to academic work, and navigating new social groups emerged. These findings provide insight into the experiences and perceptions of students repeating a nursing fundamentals course. Conclusion: Implications for nurse educators, advisers, and administrators include providing resources for student support and helping students recognize the value of seeking academic support before failing a course. Understanding students' perceptions regarding repeating a nursing fundamentals course provides valuable insight into retention efforts in undergraduate nursing programs. [ABSTRACT FROM AUTHOR]

The authors contend that building adequate validity evidence requires collaborating with stakeholders with diverse expertise (e.g. students, patients, practicing clinicians, and researchers from multiple disciplines). [ABSTRACT FROM AUTHOR]

Context: One central consideration in health professions education (HPE) is to ensure we are making sound and justifiable decisions based on the assessment instruments we use on health professionals. To achieve this goal, HPE assessment researchers have drawn on Kane's argument‐based framework to ascertain the validity of their assessment tools. However, the original four‐inference model proposed by Kane – frequently used in HPE validation research – has its limitations in terms of what each inference entails and what claims and sources of backing are housed in each inference. The under‐specification in the four‐inference model has led to inconsistent practices in HPE validation research, posing challenges for (i) researchers who want to evaluate the validity of different HPE assessment tools and/or (ii) researchers who are new to test validation and need to establish a coherent understanding of argument‐based validation. Methods: To address these identified concerns, this article introduces the expanded seven‐inference argument‐based validation framework that is established practice in the field of language testing and assessment (LTA). We explicate (i) why LTA researchers experienced the need to further specify the original four Kanean inferences; (ii) how LTA validation research defines each of their seven inferences and (iii) what claims, assumptions and sources of backing are associated with each inference. Sampling six representative validation studies in HPE, we demonstrate why an expanded model and a shared disciplinary validation framework can facilitate the examination of the validity evidence in diverse HPE validation contexts. Conclusions: We invite HPE validation researchers to experiment with the seven‐inference argument‐based framework from LTA to evaluate its usefulness to HPE. We also call for greater interdisciplinary dialogue between HPE and LTA since both disciplines share many fundamental concerns about language use, communication skills, assessment practices and validity in assessment instruments. The seven‐inference validation framework, from language assessment, is introduced to health professions education to improve validation research and promote cross‐disciplinary conversations. [ABSTRACT FROM AUTHOR]

Objective: To assess effects of Healthy Change intervention on maternal perception of her child's body weight (MPCW), maternal feeding style, and obesogenic home environment. Methods: A randomized control trial was conducted, consisting of two arms: the intervention group received the Healthy Change program, and the control group received the Hygiene and Accident Prevention program. A total of 356 mother-preschool child dyads participated, 182 in the intervention group and 174 in the control group, residing in Mexico and the United States. Data were collected at baseline and after the program through self-administered questionnaires completed by mothers and child anthropometric measurements. Results: Although no significant between-group difference in pre- and post-intervention change of MPCW was found, sub-analyses revealed that a higher proportion of mothers in the intervention group accurately perceived their child's body weight at the study endpoint using categorical (67% vs. 57.1%, p < 0.005) and visual scales (48.9% vs. 41.8%, p < 0.015). Additionally, more mothers of overweight children in the intervention group accurately perceived their children's overweight and obese status compared to those in the control group (29.8% vs. 10.3%, X2 = 4.26, df = 1, p < 0.039). The intervention group also displayed a higher proportion of mothers with authoritative feeding style (26.4% vs. 16.5%, p < 0.036) and significantly higher family nutrition and physical activity scores (29.1 vs. 28.0, p < 0.000) at the study endpoint. Conclusions for practice: Healthy Change Intervention led to improved accuracy of MPCW, a shift toward maternal authoritative feeding styles, and positive changes in obesogenic home environments. Significance: What is already known on this subject?: Mothers of overweight or obese children often underestimate their children's weight status. Research shows when mothers are unaware of their children's weight issues, they are less likely to take preventive actions, or seek health services. The most frequent maternal child feeding style in Hispanic mothers is the authoritarian, What this study adds?: Healthy Change intervention was first of its kind designed to increase mothers' awareness about their preschooler's overweight and obese status. Healthy Change promote authoritative feeding style, and favorable changes in family nutrition and physical activity. [ABSTRACT FROM AUTHOR]

In schools and programs of public health, active learning and restructured feedback strategies may improve student learning and course performance compared to traditional lecture-based formats and grading systems. To promote student engagement and active learning, we implemented the team-based learning (TBL) model and a restructured grading approach based on principles of "ungrading" in the required behavioral research methods course of a master's level public health curriculum. We conducted a quasi-experimental, mixed-methods evaluation of the implementation of restructured grading approach (two sections, n = 46) compared to the traditional grading approach (two sections, n = 34). For the restructured grading sections, numeric grades were removed for weekly team quizzes and team assignments. We administered and analyzed pre- and post-course surveys to compare perceived mastery of course learning objectives, intrinsic motivation, and perceptions of grading and instructor feedback by grading approach. Additionally, we compared course grades and final paper grades by grading approach and conducted two focus groups (one for each approach). The results indicate that students' learning, satisfaction, and perceptions of the course were mainly equivalent across grading approaches. Students in the restructured grading sections demonstrated a few modestly improved outcomes compared to their peers in the traditional grading courses. Students in the restructured grading sections had slightly higher mean course grades, reported greater increase in confidence to critically evaluate research designs, and found team quizzes to be more helpful. Removing grades for team quizzes and assignments supported student learning and reduced student stress. [ABSTRACT FROM AUTHOR]

Background: Augmented reality can provide a 3D virtual experience, widely used in modern education. However, the impact of these applications on the underdeveloped tribal community has yet to be investigated. To our knowledge, no markerless augmented reality application has been developed especially for learning the language of the Bodo tribe. Therefore, we have developed a markerless augmented reality application—BodoRao to teach the alphabet and numerals of the Bodo tribal language. Objective: This study aims to assess the usability and efficacy of the BodoRao application. To investigate how augmented reality apps affect students' academic achievement in language acquisition. Also, assess the students' attitude towards using an augmented reality application. Method: A mixed‐method approach that combined quantitative and qualitative methods was used to gather the data. A total of 80 students drawn from two user groups: native speakers and non‐native speakers were evaluated, to determine if the BodoRao application can benefit a variety of speakers. Furthermore, from each of the user groups, experimental and control groups were formed. The experimental group used an augmented reality application to learn while the control group studied using a traditional textbook. Eight teachers were also interviewed to get their opinions on the BodoRao application. Results and Conclusion: The findings found a significant difference in the achievement test results between the experimental and control groups for both native and non‐native users. Students' positive attitudes toward the application were also observed, as represented by their high application satisfaction, low anxiety and readiness for use. Additionally, it was observed that there was a positive and significant correlation between the academic achievements and attitudes of native and non‐native students in the experimental group. Lay Description : What is already known about this topic: Augmented reality has been used for educational purposes, including language acquisition.Augmented reality applications increase learning interest, motivation and engagement among learners. What this paper adds: This study develops a markerless augmented reality application—'BodoRao' for teaching a vulnerable Bodo tribal language.This is a novel technology as it is the first augmented reality application developed for teaching the Bodo language.This application will teach the Bodo language to the tribe's younger generations, helping to preserve the language at the same time.This study has done usability testing on two user groups—native and non‐native—to ascertain whether the BodoRao application can benefit a variety of speakers. Implications for practice and/or policy: More augmented reality applications should be developed for endangered languages to safeguard and educate the next generation of speakers. [ABSTRACT FROM AUTHOR]

Background: Stealth assessment is a learning analytics method, which leverages the collection and analysis of learners' interaction data to make real‐time inferences about their learning. Employed in digital learning environments, stealth assessment helps researchers, educators, and teachers evaluate learners' competencies and customize the learning experience to their specific needs. This adaptability is closely intertwined with theories related to learning, engagement, and motivation. The foundation of stealth assessment rests on evidence‐cantered design (ECD), consisting of four core models: the Competency Model (CM), Evidence Model, Task Model, and Assembly Model. Objective: The first step in designing a stealth assessment entails producing operational definitions of the constructs to be assessed. The CM establishes a framework of latent variables representing the target constructs, as well as their interrelations. When developing the CM, assessment designers must produce clear descriptions of the claims associated with the latent variables and their states, as well as sketch out how the competencies can be measured using assessment tasks. As the designers elaborate on the assessment model, the CM definitions need to be revisited to make sure they work with the scope and constraints of the assessment. Although this is the first step, problems at this stage may result in an assessment that does not meet the intended purpose. The objective of this paper is to elucidate the necessary steps for CM development and to highlight potential challenges in the process, along with strategies for addressing them, particularly for designers without much formal assessment experience. Method: This paper is a methodological exposition, showcasing five examples of CM development. Specifically, we conducted a qualitative retrospective analysis of the CM development procedure, wherein participants unfamiliar with ECD applied the framework and showcased their work. In a stealth assessment course, four groups of students (novice stealth assessment designers) engaged in developing stealth assessments for challenging‐to‐measure constructs across four distinct projects. During their CM development process, we observed various activities to pinpoint areas of difficulty. Results: This paper presents five illustrative examples, including one for assessing physics understanding and four for the development of CMs for four complex competencies: (1) systems thinking, (2) online information credibility evaluation, (3) computational thinking, and (4) collaborative creativity. Each example represents a case in CM development, offering valuable insights. Conclusion: The paper concludes by discussing several guidelines derived from the examples discussed. Emphasizing the importance of dedicating ample time to fine‐tune CMs can significantly enhance the accuracy of assessments related to learners' knowledge and skills. It underscores the significance of qualitative phases in crafting comprehensive stealth assessments, such as CMs, alongside the quantitative statistical modeling and technical aspects of these assessments. Lay Description: What is currently known about this topic?: Stealth assessment represents an unobtrusive, automated formative assessment method.This method uses learning analytics within digital learning environments (e.g., games).The main purpose is to assess and foster the competencies of diverse learners. What does this paper add?: This paper serves as a conceptual and methodological guide.This paper focuses on the critical process of competency model development.Competency model development is a crucial step in the creation of stealth assessments. Implications for practice/or policy: Learning scientists and assessment designers can leverage this paper as a resource.Assessment designers can benefit from this paper and see various examples of the process. [ABSTRACT FROM AUTHOR]

Background: Sound learning design should be based on the constructive alignment of intended learning outcomes (LOs), teaching and learning activities and formative and summative assessment. Assessment validity strongly relies on its alignment with LOs. Valid and reliable formative assessment can be analysed as a predictor of students' academic performance, but the question is how significant its predictive power is, and what other elements can affect predictions. Objectives: Our aim was to investigate the predictive power of formative assessment for summative assessment, measuring the acquisition of LOs. Methods: We analysed formative assessment results (quizzes, homework), together with log data (video and other material use, class attendance), to determine the most influential predictors and establish a reliable predictive learning analytics model. We used the Random Forest algorithm. The model is based on the data from two university mathematical courses, delivered at different years and levels of study, incorporating 813 students in two consecutive years. Results and Conclusions: Our results show that formative assessment, together with previous summative assessment, is a stronger predictor of summative assessment results than other data on students' engagement. The study pointed to the importance of completeness and quality of data, and clear links between assessment and LOs when making predictions of student results. It suggested that predictions are less reliable for the lowest and the highest performing students. It was noted that other factors can also affect predictions, like the level of LOs, or factors not easily extracted from digital data, like the learning environment and individual students' strategies. Lay Description: What is currently known about this topic?: When educators design lessons, they aim for students to acquire intended learning outcomes.To know if students are making progress, educators use a mix of regular checks, like quizzes (formative assessment) and major exams (summative assessment).Predictive learning analytics may contribute to sound learning design (LD). What does this paper add?: In our study, we looked into whether these regular checks can predict how a student might perform on high‐stake exams.We collected data from students taking two university maths courses, including their scores on quizzes, their attendance, and their use of study materials.Using a machine learning technique called the Random Forest algorithm, we built a model to predict student exam scores.Our results indicate that formative assessment is the best predictor of the success in summative assessment. Implications for practice/or policy: We found that how a student performs on regular checks is a good sign of how they might do on the high‐stake exam and careful preparation of assessment and whole LD help student learning.Assessment, formative as well as summative, needs to be aligned with intended learning outcomes and only in this case results can inform quality assurance processes and the restructuring of LD.There are other personal factors that can influence a student's performance, which are not easy to spot just from the digital data we have.The complexity of what is being taught plays a role in predicting students' final scores. [ABSTRACT FROM AUTHOR]

Background: Although gender inequality in education is gaining increasing attention, female underrepresentation remains pervasive in STEM fields. Many studies have applied various interventions to narrow the gender gap in STEM education. Objectives: In this study, we conducted a systematic meta‐analysis to examine the effectiveness of various interventions for gender equality in STEM education and tested the influence of moderator variables. Methods: Ten databases—ERIC, IEEE, JSTOR, ProQuest‐Education, SAGE Journals, Scopus, Springer Link, Taylor & Francis, Web of Science, and Wiley Online Library—and seven high‐quality journals in related fields were selected as literature resources. The Preferred Reporting Items for Systematic Reviews and Meta‐analyses (PRISMA) process was used to identify eligible articles for the random‐effects meta‐analysis. Results and Conclusions: The overall effect size (Hedges' g) was 0.434, indicating that the interventions promoting gender equality in STEM education had a near‐medium positive effect. There were significant differences by the type of intervention, but not by the type of intervention outcome. The results of the moderator analysis showed a significant difference in moderator variables, including country, educational level, form of experiment, intervention level, and different measurement methods, whereas there was no significant difference in the moderator variables, including economic development level and sample size. Implications: This study examined the effectiveness of gender equality interventions and the impact on it of different types of intervention, intervention outcomes, and moderator variables. These results have implications for the design of gender equality interventions in STEM education. Lay Description: What is already known about this topic: Gender equality in STEM education is valuable in reducing barriers and underrepresentation of female students.Different interventions have been applied to promote gender equality, but their effectiveness varies. What this paper adds: In STEM education, there were significant differences among the different types of interventions, but not among the different types of intervention outcomes.This study tested the significance of the moderating effect of the moderator variables in the gender equality intervention on the effectiveness of the intervention, including economic development level (developed or developing country), country, educational level, sample size, form of experiment, intervention level, and measurement method. Implications of study findings: Among the different types of interventions, those by different teachers and interpersonal interactions were the most effective.The results of the moderator analysis at the intervention level showed that the effectiveness of the interventions at the environmental level was significantly greater than that at the individual level.The study holds specific implications for the design of interventions for gender equality in STEM education. [ABSTRACT FROM AUTHOR]

Background: Project‐based collaborative learning (PBCL) is a technique that supports knowledge and skill development through complex, real‐world projects. Understanding factors that influence group performance in PBCL, such as gender composition, is crucial. Objectives: This study investigates the impact of gender composition on group performance in PBCL, specifically focusing on the critical thinking, creativity, communication, and collaboration (4Cs) 21st‐century learning skills. Methods: A total of 312 students were divided into distinct Python programming groups for the experiment. Group performance was assessed using an agglomerative clustering algorithm guided by the ontological group learner model, which examined gender composition, communication patterns, collaboration strategies and project assessment outcomes. Results and Conclusion: Gender‐balanced groups demonstrated positive outcomes in the 4Cs skills, with groups containing a greater proportion of women exhibiting superior performance in collaboration and communication, whereas majority‐male groups performed relatively poorer across all skills. Notably, in the context of PBCL, the presence of more women in small groups enhanced the 4Cs skills project assessment outcomes. Takeaways: Future research should focus on providing effective support for male online learners in developing the 4Cs skills. The findings offer insights and recommendations for group formation in collaborative learning, facilitating the design of inclusive and impactful learning environments. Lay Description: What is (not) known about the subject matter?: Assessment may be influenced by diverse perspectives on group work practices, such as what constitutes valuable involvement in a collaborative process. In light of this, gender composition must be taken into account when interpreting evaluation results.Little is known about the effect of gender composition on group assessment results, particularly in the context of project‐based collaborative learning. What is the contribution of this paper?: 312 pupils enrolled in our institution's introductory programming course took part in the experiment. The students were grouped into varied, small groups based on their Python programming abilities.We developed semantic web technologies to define the characteristics and accomplishments of groups in terms of the 4Cs of 21st‐century learning skills.We deployed ontological models to characterize the data we gathered about our learners' groups and their performance on assessments.Using an agglomerative clustering machine learning algorithm, we categorized groups based on the results of the assessment of the proposed collaborative project. What are the implications of the findings?: The findings indicate that groups with a greater proportion of women achieve outcomes that are superior to those obtained by groups with an equal gender split, particularly in terms of collaborations and communications.The greater the number of women in a small group, the better the project assessment results for the 4Cs 21st‐century learning skills in a PBCL setting.In future research, we should make inferences based on the ontological models to reason about assessment data by executing logical rules and then analysing them in order to develop an intelligent assessment environment.Also, we should concentrate on how to provide male e‐learners with high‐quality 4Cs support. We might additionally examine the potential effects of gender variations on the performance of large groups. [ABSTRACT FROM AUTHOR]

Background: Learning Progress Assessments (LPA) have been developed to help teachers individualize their curriculum. The use of LPA is facilitated by an increasing number of computerized LPA tools. However, little is known about student factors that influence the effectiveness of computerized LPA. Objectives: In this study, we explored whether a computerized LPA that focused on reading comprehension was differentially effective depending on students' initial reading comprehension abilities. Moreover, effects of the LPA implementation on underlying or related form‐based literacy skills (i.e., decoding, spelling) were explored. Methods: The development of reading and spelling skills of 668 third graders was assessed in 41 LPA and 36 control classes in a pretest–posttest design. We used multi‐level modelling to analyse effects of the LPA on reading comprehension, decoding, and spelling skills, and tested whether these effects were qualified by students' initial achievement level. Results: The LPA treatment proved beneficial for improving reading comprehension but not for improving decoding or spelling. Children with low levels of reading comprehension at the beginning of the school year benefitted particularly from LPA. Takeaways: Teachers seem to make use of the data offered by the computerized LPA to identify children with reading comprehension difficulties. For these children, an accelerated increase in reading comprehension ability was observed. Results also suggest that this effect is specific to the literacy skill measured by the LPA and does not generalize to underlying or related literacy skills (i.e., decoding, spelling). Lay Description: What do we know?: Computerized Learning Progress Assessments (LPA) help educators to individualize their teaching.An increasing number of computerized LPA tools facilitate the use in daily routines.LPAs are orientated on skills that are relevant for the current curriculum.Many studies have shown the effectiveness of the use of LPA in reading education. What does our study add?: We know little about student factors that influence the effectiveness of LPA.We studied the effects of LPA in a study with 668 third graders.Our results show that this specific LPA treatment proved beneficial for improving curricular skills like reading comprehension but not for improving underlying or related skills like decoding or spelling.Children with low levels of reading comprehension at the beginning of the school year benefitted particularly from computerized LPA. What implications does our study have for practitioners?: Our results suggest that teachers used the data offered by the Computerized LPA to identify children with reading comprehension difficulties – a curricular skill.The use of computerized LPA seems to help teachers support children who have deficits in specific curricular skills that correspond with the type of LPA assessment.However, children with other reading‐related difficulties are not necessarily detected.Maybe a combination of computerized tools could solve this issue in the future. [ABSTRACT FROM AUTHOR]

Background: During the past decade, the increasingly heterogeneous field of learning analytics has been critiqued for an over‐emphasis on data‐driven approaches at the expense of paying attention to learning designs. Method and objective: In response to this critique, we investigated the role of learning design in learning analytics through a systematic literature review. 161 learning analytics (LA) articles were examined to identify indicators that were based on learning design events and their associated metrics. Through this research, we address two objectives. First, to achieve a better alignment between learning design and learning analytics by proposing a reference framework, where we present possible connections between learning analytics and learning design. Second, to present how LA indicators and metrics have been researched and applied in the past. Results and conclusion: In our review, we found that a number of learning analytics papers did indeed consider learning design activities for harvesting user data. We also found a consistent increase in the number and quality of indicators and their evolution over the years. Lay Description: What is already known about this topic?: Learning design (LD) is the pedagogic process used in teaching/learning that leads to the creation and sequencing of learning activities and the environment in which it occurs.Learning analytics (LA) is the measurement, collection, analysis & reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.There are multiple studies on the alignment of LA and LD but research shows that there is still room for improvement. What this paper adds?: To achieve better alignment between LD and LA. We address this aim by proposing a framework, where we connect the LA indicators with the activity outcomes from the LD.To demonstrate how learning events/objectives and learning activities are associated with LA indicators and how an indicator is formed/created by (several) LA metrics. We address this aim in our review.This article also aims to assist the LA research community in the identification of commonly used concepts and terminologies; what to measure, and how to measure. Implications for practice and/or policy: This article can help course designers, teachers, students, and educational researchers to get a better understanding on the application of LA.This study can further help LA researchers to connect their research with LD. [ABSTRACT FROM AUTHOR]

This study aimed to investigated the impact of Kahoot, ChatGPT, and traditional teaching methods on nursing students' sexual health knowledge and attitudes. This quasi-experimental study was conducted using an online survey of 93 nursing students. Data collection instruments were implemented in three stages: pre-test, post-test, and follow-up test, measuring students' levels of sexual health knowledge and attitudes. The training was conducted over a total of four hours, consisting of two hours per week for each group. Data were collected through tests prepared via Google Forms. After the training, it was observed that students in all three groups found the educational program beneficial and effective. In the follow-up test, students reported an increase in their confidence in managing sexual health-related issues. Statistical analyses indicated that the training delivered through Kahoot and ChatGPT was more effective in improving sexual health knowledge levels. At the same time, traditional education was more effective in improving sexual health attitudes by the end of the first month. The analyses also revealed that the change in students' sexual health knowledge levels did not significantly differ among different educational methods (Kahoot, ChatGPT, and traditional education). Kahoot and ChatGPT educational technologies were effective in improving nursing students' sexual health knowledge levels in repeated measurements. However, when considering the change between measurements, different educational methods had similar effects on sexual health knowledge levels and sexual health attitudes. [ABSTRACT FROM AUTHOR]

Background: Early numeracy interventions including basic arithmetic are crucial for young students at risk for early mathematics difficulties (MDs), yet few studies have evaluated numeracy interventions in second grade with a randomized controlled design. Aim: This pre‐ and post‐test randomized controlled study evaluated the effects of an intensive 9‐week numeracy and arithmetic programme for second‐grade students at risk for early MDs. The focus of the programme was students' foundational understanding of numbers and mathematical concepts and procedural fluency with arithmetic tasks. Sample: A total of 753 first‐grade students from 21 schools in Sweden were screened for low achievement in number knowledge and arithmetic. Methods: Students considered at risk for MDs (≤25 percentile on two consecutive first‐grade mathematics screenings) were individually randomized to an intervention group (n = 32) or control group (n = 30) at the beginning of second grade (7–8 years old). Trained teachers administered the one‐to‐one, explicit programme to intervention group students in elementary school settings. The intervention group received numeracy instruction emphasizing foundational mathematics concepts and procedures. Controls received teaching as usual with potential special education support provided by their schools. Results: The intervention group demonstrated significantly greater improvements in conceptual knowledge, arithmetic calculations and problem‐solving compared to the control group, with medium size effects observed. Conclusions: A supplemental and intensive programme, with explicit instruction emphasizing numeracy, substantially improved knowledge and skills essential for arithmetic learning. Instruction in conceptual number knowledge and procedures also shows a significant impact on basic arithmetic problem‐solving. [ABSTRACT FROM AUTHOR]

A psychological framework for different types of items commonly used with mixed-format exams is proposed. A choice model based on signal detection theory (SDT) is used for multiple-choice (MC) items, whereas an item response theory (IRT) model is used for open-ended (OE) items. The SDT and IRT models are shown to share a common conceptualization in terms of latent states of "know/don't know" at the examinee level. This in turn suggests a way to join or "fuse" the models—through the probability of knowing. A general model that fuses the SDT choice model, for MC items, with a generalized sequential logit model, for OE items, is introduced. Fitting SDT and IRT models simultaneously allows one to examine possible differences in psychological processes across the different types of items, to examine the effects of covariates in both models simultaneously, to allow for relations among the model parameters, and likely offers potential estimation benefits. The utility of the approach is illustrated with MC and OE items from large-scale international exams. [ABSTRACT FROM AUTHOR]

For essay-writing tests, challenges arise when scores assigned to essays are influenced by the characteristics of raters, such as rater severity and consistency. Item response theory (IRT) models incorporating rater parameters have been developed to tackle this issue, exemplified by the many-facet Rasch models. These IRT models enable the estimation of examinees' abilities while accounting for the impact of rater characteristics, thereby enhancing the accuracy of ability measurement. However, difficulties can arise when different groups of examinees are evaluated by different sets of raters. In such cases, test linking is essential for unifying the scale of model parameters estimated for individual examinee–rater groups. Traditional test-linking methods typically require administrators to design groups in which either examinees or raters are partially shared. However, this is often impractical in real-world testing scenarios. To address this, we introduce a novel method for linking the parameters of IRT models with rater parameters that uses neural automated essay scoring technology. Our experimental results indicate that our method successfully accomplishes test linking with accuracy comparable to that of linear linking using few common examinees. [ABSTRACT FROM AUTHOR]

Over the last two decades, the analogue report task has become a standard method for measuring the fidelity of visual representations across research domains including perception, attention, and memory. Despite its widespread use, there has been no methodical investigation of the different task parameters that might contribute to response variability. To address this gap, we conducted two experiments manipulating components of a typical analogue report test of memory for colour hue. We found that human response errors were independently affected by changes in storage and maintenance requirements of the task, demonstrated by a strong effect of set size even in the absence of a memory delay. In contrast, response variability remained unaffected by physical size of the colour wheel, implying negligible contribution of motor noise to task performance, or by its chroma radius, highlighting non-uniformity of the standard colour space. Comparing analogue report to a matched forced-choice task, we found variation in adjustment criterion made a limited contribution to analogue report variability, becoming meaningful only with low representational noise. Our findings validate the analogue report task as a robust measure of representational fidelity for most purposes, while also quantifying non-representational sources of noise that would limit its reliability in specialized settings. [ABSTRACT FROM AUTHOR]

This work investigates the piercing of microholes in turbine shroud rings (Inconel-625) using the Abrasive Waterjet Cutting process. The concern with the hole piercing is the kerf angle caused by the attenuation of the jet energy and stand-off distance, which seriously impacts the processing precision of abrasive water jet piercing. The effects of piercing parameters like machining time (40, 60 and 80 s), abrasive mesh size (80 mesh and 120 mesh), stand-off distance (1, 2, 3 and 4 mm), abrasive jet pressure (100, 125, 150 and 175 MPa) are studied to reduce the kerf angle. The kerf angle increased linearly with a stand-off distance increase at different machining times. By piercing for 60 s and 80 s, the lowest values of kerf angle are obtained (0.03∘ and 0.02∘). The optimum conditions for making a pierced hole with a minimum kerf angle of 0.02∘ were achieved with a machining time- of 60 s, abrasive mesh size- of 20 mesh, and abrasive jet pressure- of Scanning electron microscope (SEM) images and visual measuring system (VMS) images are used to identify the surface characteristics in kerf zone. The features, including ploughing, particle embedment, lip impression and wear path due to the ductile mode of erosion caused by high energy impact, is also discussed. [ABSTRACT FROM AUTHOR]

Introduction.: The use of strategic learning strategies has been positively associated with academic performance in several graduate health profession programs. This finding suggests that it may be an important construct to explore in Doctor of Physical Therapy (DPT) education. The Learning and Study Strategies Inventory (LASSI) summarizes a student's perception and use of 10 learning and study strategies. Review of Literature.: Although the LASSI has limited reporting in DPT education, other health care education programs have shown correlation with academic performance. The purpose of this study was to examine DPT students' early perceptions of strategic learning with descriptive summaries of LASSI data and examine correlations between demographic and admissions-related data. Subjects.: Matriculated DPT students (n = 294) at a 2-year hybrid program who completed the LASSI at orientation in 2020 and 2021. Methods.: This was a descriptive study that retrospectively analyzed LASSI scores in entry-level DPT students. LASSI score differences among demographic groups and Spearman's rho correlations between the LASSI, Graduate Record Examination (GRE) scores, grade point averages, grit, and emotional intelligence (EI) were explored. Results.: LASSI score means were in the 50th–75th percentile (moderate category) suggesting a need for further development in strategic learning. Group differences in LASSI scores were noted for gender identity (male higher Anxiety management, P <.001; female higher Attitude , P <.001, Time Management , P =.003, and Use of Academic Resources , P =.003), racial–ethnic minoritized group (higher S elf-regulation , P =.013), first-generation college students (higher Attitude , P =.047), physical therapy assistants (higher Information Processing , P =.047), students with a primary language other than English (higher Time Management , P =.046), and older students (higher Anxiety management, P =.026). Weak but significant correlations were identified between LASSI scale and component scores and several admissions variables. Highest correlations were with grit (Will , ρ = 0.319, P <.001; Concentration , ρ = 0.312, P <.001), EI (Will , ρ = 0.328, P <.001; Attitude , ρ = 0.302, P <.001; Self-regulation , ρ = 0.382, P <.001; Use of Academic Resources ρ = 0.331, P <.001), and quantitative GRE scores (Anxiety management, ρ = 0.341, P <.001). Discussion/Conclusion.: All LASSI scale scores and components were in the moderate category, potentially indicating a need to coach and develop strategic learning strategies. Group differences in LASSI scores may represent varied student needs. The weak relationship between LASSI scores and admissions variables could suggest that the constructs measured by LASSI are not currently captured through typical DPT admissions practices. [ABSTRACT FROM AUTHOR]

Supplemental Digital Content is Available in the Text. Introduction.: Integrated clinical education (ICE) courses require opportunities for practice, assessment of performance, and specific feedback. The purposes of this study were to 1) analyze the internal consistency of a tool for evaluating students during ICE courses, 2) examine the responsiveness of the tool between midterm and final assessments, and 3) develop a model to predict the final score from midterm assessments and explore relationships among the 6 domains. Review of Literature.: Several clinical education assessment tools have been developed for terminal clinical experiences, but few have focused on the needs of learners during the ICE. Subjects.: Eighty-five student assessments were collected from 2 consecutive cohorts of physical therapist students in a first full-time ICE course. Methods.: The tool contained 29 items within 6 domains. Items were rated on a 5-point scale from dependent to indirect supervision. Cronbach's alpha was used to analyze the internal consistency of the tool, whereas responsiveness was examined with paired t -test and Cohen's d. A best subsets regression model was used to determine the best combination of midterm variables that predicted the final total scores. Coefficients of determination (R 2) were calculated to explore the relationships among domains. Results.: The tool was found to have high internal consistency at midterm and final assessment (α = 0.97 and 0.98, respectively). Mean scores increased over time for each domain score and for the total score (P <.001; d = 1.5). Scores in 3 midterm domains predicted more than 57% of the variance in the final total score. Discussion and Conclusion.: Results support the use of this tool to measure student performance and growth in a first full-time ICE course. Targeted measurement of students' abilities in ICE courses assists with differentiating formative and summative learning needed to achieve academic success. [ABSTRACT FROM AUTHOR]

Quantifying image quality in the absence of a reference image continues to be a challenge despite the introduction of numerous no-reference image quality assessments (NR-IQA) in recent years. Unlike most existing NRIQA methods, this paper proposes an efficient NR-IQA method based on deep visual interpretations. Specifically, the main components of the proposed method are: i) generating a pseudo-reference image (PRI) for the input distorted images, ii) employing a pretrained convolutional network to extract feature maps from the distorted image and the corresponding PRI, iii) producing visual explanation images (VEIs) by using the feature maps of the distorted image and the corresponding PRI, iv) measuring the similarity between the two VEIs using an image similarity metric, and v) employing a non-linear mapping function for quality score alignment. In our experiments, we evaluated the efficacy of the proposed method across various forms of distortion using four benchmark datasets (LIVE, SIQAD, CSIQ, and TID2013). The proposed approach demonstrates parity with the latest methods, as evidenced by comparisons with both hand-crafted NR-IQA and deep learning-based approaches. [ABSTRACT FROM AUTHOR]

A critically important balance in educational measurement between practical concerns and matters of technique has atrophied in recent decades, and as a result, some important issues in the field have not been adequately addressed. I start with the work of E. F. Lindquist, who exemplified the balance that is now wanting. Lindquist was arguably the most prolific developer of achievement tests in the history of the field and an accomplished statistician, but he nonetheless focused extensively on the practical limitations of testing and their implications for test development, test use, and inference. I describe the withering of this balance and discuss two pressing issues that have not been adequately addressed as a result: the lack of robustness of performance standards and score inflation. I conclude by discussing steps toward reestablishing the needed balance. [ABSTRACT FROM AUTHOR]

Reading disorders, including reading comprehension disorders, are among the most common referrals for evaluation in schools. If that evaluation involves individually administered tests of reading, the examiner is faced with selecting at least one reading comprehension subtest that is inherently associated with specific task demands, such as a cloze procedure or a story retell procedure. This study explored the correlates of performance of these two types of reading comprehension measures in lower grades (i.e., grades 1–5) and upper grades (i.e., grades 6–12). Results revealed a moderate correlation between these two tasks and evidence that students with reading disorders may perform poorer on cloze reading comprehension measures than story retell measures in both grade groupings. Regression analyses revealed that variance in each reading comprehension task is associated with a unique grouping of predictor variables that are associated with the Big Five of Reading and short-term/working memory. Discussion focuses on the implications of these findings for the evaluation of students with suspected disabilities and research. [ABSTRACT FROM AUTHOR]

The pandemic has altered accounting education with the widespread adoption of remote evaluation platforms. We apply the lens of the fraud triangle to consider how the adoption of remote evaluation influences accounting students' ethical values by measuring the incidence of cheating behavior as well as capturing their perceptions of their opportunity to cheat and their rationalization of cheating behavior. Consistent with prior research, our results show that cheating is higher in the online environment compared to remote evaluation, although the use of proctoring software in online evaluation appears to mitigate but not eliminate students' the unethical behavior. However, cheating was not reduced when students attest to an honor code during the beginning of an exam. Nonetheless, we find that the use of both proctoring software and honor codes reduces students' perceptions of opportunity and rationalization of cheating behavior. It follows that the remote evaluation environment may unintentionally be negatively influencing the ethicality of students and future accounting professionals by promoting cheating behavior and, by so doing, negatively influencing the development of unethical values of accounting students and future accounting professionals. Educators should consider the use of appropriate educational interventions to reduce the incidence and opportunities for unethical behavior and, by so doing, help promote the development of ethical values in future accounting professionals. Further implications for teaching and the accounting profession are discussed. [ABSTRACT FROM AUTHOR]

Large language models are increasingly used in educational and psychological measurement activities. Their rapidly evolving sophistication and ability to detect language semantics make them viable tools to supplement subject matter experts and their reviews of large amounts of text statements, such as educational content standards. This paper presents an application of text embeddings to find relationhips between different sets of educational content standards in a content mapping process. Content mapping is routinely used by state education agencies and is often a requirement of the United States Department of Education peer review process. We discuss the educational measurement problem, propose a formal methodology, demonstrate an application of our proposed approach, and provide measures of its accuracy and potential to support real‐world activities. [ABSTRACT FROM AUTHOR]

The article discusses the evolution of item development in educational assessments, focusing on large-scale K-12 assessments. It highlights the importance of item quality, the role of item writers, and the review processes involved in ensuring fairness and validity. The Standards for Educational and Psychological Testing have guided best practices in item development since 1966, emphasizing the critical role of items in score interpretations and decision-making. The article also explores the potential impact of artificial intelligence (AI) and large language models (LLMs) on future item development, emphasizing the need for human judgment and validation in technology-based processes. [Extracted from the article]

In 2023, a National Council on Measurement in Education Presidential Task Force developed a consensus framework for foundational competencies in educational measurement to guide graduate programs and subsequent professional development. This article elaborates on the social, cultural, historical, and political context subdomain from that framework. A graduate course on the history of testing and testing policy in the United States is proposed to help measurement professionals develop an understanding of historic belief systems and theories of action that affect every aspect of testing applications—definition of constructs, instrument design, respondents’ interactions, interpretations and use of results, and both intended and unintended consequences. Two, accessible, key readings are proposed for each of 14 weeks addressing the following topics: IQ testing and deficit perspectives; special education placements, disproportionality, and accommodations; grade retention and tracking; college admissions testing; standards‐based reforms; 1990s performance assessment innovations; NCLB and school accountability; achievement gaps and opportunity to learn; NAEP and international assessments; standard setting and NAEP achievement levels; Common Core State Standards and ESSA; formative assessment and research on learning; culturally responsive assessment. [ABSTRACT FROM AUTHOR]

Background Aims Sample and Methods Results Conclusions Previous research has demonstrated that quizzing can improve self‐regulation processes and learning performances. However, it remains unclear whether quizzes in multimedia material bring similar benefits, and whether interindividual differences such as working memory capacity (WMC) modulate quizzing effects.This study aimed to examine the effects of embedded quizzes (multiple quizzes within the learning sequence) with feedback during a multimedia learning sequence on self‐regulated processing (monitoring and control) and learning performances on repeated (material already tested) and new (untested) questions, and possible WMC moderation on performances.Participants were 59 students who learned a multimedia neuroscience course module in either a no‐quiz or embedded quizzes condition. With regard to self‐regulated processing, control was assessed with eye‐tracking measures (fixation durations and transitions between texts and illustrations), and monitoring by comparing self‐reported judgements of learning with actual performances (calibration). At the end, students' WMC was measured, and learning performances were assessed with repeated and new questions.Quizzing improved learning performances on repeated and new questions, and enhanced monitoring (better calibration). Students with low WMC benefited more from quizzing for new questions than those with high WMC. However, contrary to our hypothesis, the embedded quizzes group allocated less time to the learning than the no‐quiz group.Embedded quizzes are relevant tools to help students recalibrate their monitoring process and foster more effective self‐regulated learning. Results confirm that the use of quizzes can be recommended to improve the learning of multimedia material, especially among students with low WMC. [ABSTRACT FROM AUTHOR]

The article discusses the transition of college admissions testing from mandated to test-optional policies in the United States. It explores the historical background of standardized testing, the impact of test-optional policies on diversity and equity, and the challenges and considerations associated with admissions testing. The text raises questions about the fairness, validity, and predictive nature of standardized tests, as well as the implications of test-optional policies on college rankings and student access to higher education. It also highlights the need for further research and thoughtful implementation of alternative admission processes to ensure fairness and inclusivity in college admissions. [Extracted from the article]

Recent shifts in nursing education towards generic proficiencies pose challenges to the unique demands of mental health nursing education. Student mental health nurses at the authors' higher education institution (HEI) have provided service feedback that has expressed the difficulties they have encountered. This article examines the issues faced by students, assessors and educators in interpreting and applying the proficiency standards set by the Nursing and Midwifery Council. Addressing the complexities of mental health nursing education, as well as the barriers to learning and attainment, requires a collaborative effort and innovative solutions if HEIs are to successfully prepare future mental health nurses to meet the evolving demands of their role. The proposed solution is a 'Proficiency Directory', which provides structured resources for mental health nursing students to align learning experiences with assessment criteria, facilitating a more comprehensive and meaningful learning journey. [ABSTRACT FROM AUTHOR]

Background: The purpose of the present study was to evaluate the use of a free online continuing education (CE) course that sought to address barriers of capability by training dental team members in the specific recommendations of the American Dental Association (ADA)-endorsed adult guideline for the pharmacologic management of acute dental pain, shared decision-making, and the adoption of the guideline into practice. Methods: In 2022 and 2023, dentists completed an online, asynchronous CE course on the guideline-concordant pharmacologic management of acute dental pain. They completed 11-item knowledge tests before and after completing the course. Total scores on the pre- and post-tests were compared using a t-test. Results: The mean score increased from 7.68 (SD = 1.08) on the pretest to 8.79 (SD = 1.35) on the post-test (t(4468) = -27.34, p <.01), indicating that dentists gained knowledge from the CE course. Conclusions: We found that the CE course increased knowledge with respect to the guideline recommendations and shared decision-making but not epidemiology or incorporating a guideline into practice. Future studies should evaluate whether the CE course increased guideline-concordant prescribing. [ABSTRACT FROM AUTHOR]

This study compares the optical quality of zonal refractive multifocal and diffractive bifocal intraocular lenses (IOLs) and visual outcomes after implantation in 93 patients(93 eyes) with cataracts and high myopia. A retrospective analysis was conducted to measure visual acuity at far, intermediate, and near distances, defocus curves, wavefront aberrations, modulation transfer function (MTF), a Quality of Vision questionnaire (QoV) and visual quality self-evaluation were examined at 3 months. The results demonstrated the ZMB group showed better uncorrected near visual acuity (P < 0.01), and the MF15 group showed better uncorrected intermediate visual acuity (P < 0.001). The ZMB group provided better MTF than the MF15 group (P < 0.01) but demonstrated a worse QoV score, especially for the severity of glare, halo, and starburst (P < 0.05). The satisfaction score and spectacle independence rate in the ZMB group were higher than in the MF15 group (P < 0.01). LS-313MF15 and TecnisZMB00 offered excellent visual restoration, stable distance visual acuity, and good subjective visual function. [ABSTRACT FROM AUTHOR]

Early mathematics skills are predictive of later achievement, but there is evidence teachers generally provide little mathematics instruction in preschool classrooms. We conducted this survey study to better understand teachers' reported beliefs about their own mathematics skills, expectations, and practices for children with and without disabilities, and the impact of these reported beliefs and practices on the perceived effectiveness of their instruction. We found teachers had less confidence in their own mathematics skills than their mathematics teaching abilities and had differing expectations for children with and without disabilities. Their beliefs about their own mathematics abilities predicted their perceived effectiveness for typically developing children only, but their beliefs about their teaching abilities predicted their perceived effectiveness for children with and without disabilities. Implications include the need to better prepare and support teachers to teach mathematics to all children and collect data from varied sources on teachers' practices. [ABSTRACT FROM AUTHOR]

Background: The optimal selection process for basic physician trainees (BPTs) is unclear. Aims: To assess an adult BPT selection process, including a standardised recruitment interview assessing clinical decision‐making and situational judgement. Methods: A retrospective multi‐year cohort study of applicants who were selected for interview during the annual recruitment for 2011–2015 clinical years in an adult basic physician training network in NSW. The predictive capacity of the final recruitment assessment score was compared with success in the Royal Australasian College of Physicians (RACP) adult medicine clinical examination within 2 years. Results: Four hundred thirty‐six applicants were selected for interview (84–91 in each year). Summary mean post‐interview scores ranged from 1.25 to 10, with the median ranging between 7 and 8. Median scores were higher in those who passed the examination than those who did not (7.75 vs 6.43, P < 0.0001). Those who did not sit for the examination in the relevant year or never sat for the examination had similar median scores (7 vs 6.75, P = 0.11). Those not deemed eligible for recruitment were less likely to pass the clinical examination within 2 years than those on the eligibility list (odds ratio (OR) = 0.38, 95% confidence interval (CI) = 0.25–0.57). Applicants with mean scores lower than 8 were less likely to pass than those in the top band (8.1–10); scores between 6.1 and 8 OR 0.42 (95% CI = 0.26–0.68), 4.1–6 OR 0.23 (95% CI = 0.13–0.41) and 2.1–4 OR 0.24 (95% CI = 0.10–0.60). Conclusion(s): The predictive capacity of the selection process for success in the RACP clinical examination within the minimum time period is high. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence models such as ChatGPT (Open AI) have performed well on the exams of various medical and surgical fields. It is not yet known how ChatGPT performs on similar metabolic and bariatric surgery (MBS) questions. Objective: Assess the performance of ChatGPT on Focused Practice Designation in Metabolic and Bariatric Surgery board-style questions. Setting: United States. Methods: Questions obtained from the largest commercially available bank of FPD-MBS practice questions were entered into ChatGPT-4, as is, without prior training. We assessed the overall percentage correct as well as the percentage correct within each of the five American Board of Surgery (ABS) question categories. One-way ANOVA was used to determine if the frequency of correct answers differed between categories. Results: Out of 255 questions, ChatGPT-4 correctly answered 189 (74.1%). Between the five question categories there was no difference between the frequency of correct answers (p = 0.22). It did not matter if questions were entered individually or in groups of up to 10. Conclusion: Without prior training, ChatGPT-4 scored highly when evaluated on the largest practice question bank for the FPD-MBS exam. [ABSTRACT FROM AUTHOR]

Simulation training in healthcare settings has become a valuable training tool. It provides an ideal formative assessment for interdisciplinary teaching. It provides a high fidelity and highly immersive environment where healthcare staff and students can practice developing their skills in a safe and controlled manner. Simulation training allows staff to practice skills that better prepare them for clinical emergencies, therefore possibly optimising clinical care. While the benefits of simulation education are well understood, establishing a programme for use by critical care staff is complex. Complexities include the highly specialised scenarios that are not typically encountered in non-critical care areas, as well as the need for advanced monitoring equipment, ventilation equipment etc. These 12 tips are intended to assist healthcare educators in navigating the complexities in the establishment of a critical care simulation programme, providing advice on selecting target audiences, learning outcomes, creating a critical care simulation environment and recommendations on evaluation and development of the programme. [ABSTRACT FROM AUTHOR]

Background: Near-peer teaching is increasingly used in medical education, supporting or replacing faculty teaching. It has positive aspects for learners and tutors, some of which are explained by higher social and cognitive congruence between learners and near-peer tutors (NPTs). This study investigates the optimal combination of faculty tutors (FTs) and NPTs in an abdominal ultrasound course. Methods: Sixty-four third-year medical students underwent a basic ultrasound course, with 75% of lessons taught by NPTs and 25% by FTs. Each of four groups had a different faculty teaching timing. A mixed methods approach used a survey and semi-structured interviews at the course end to elicit learners' preferences, and end-of-course examination scores to look for differences in outcomes. Results: Most learners preferred having faculty teaching in the second half of the course, saying it would be overwhelming to start with FTs. Learners preferred between a quarter and a third of the teaching to be from FTs, with NPTs rated better at teaching basics, and FTs contributing unique, helpful clinical knowledge. There was no significant between-group difference in examination scores. Conclusions: Medical students preferred most of their teaching to be from NPTs, with some faculty input in the second half of the course. [ABSTRACT FROM AUTHOR]

Purpose: To determine if supplementing standard clinical assessments with Optical Coherence Tomography (OCT) imaging of the crystalline lens improves the accuracy and precision of lens opacity assessment and associated clinical management decisions by optometrists. Methods: Fifty optometrists registered in the UK or Éire undertook a clinical vignette study where participants graded lens opacities and made associated clinical management decisions based on the image(s)/information displayed. Three forms of vignettes were presented: (1) Slit‐lamp (SL) images of the lens, (2) SL and OCT images and (3) SL, OCT and visual function measures. Vignettes were constructed using anonymised data from 50 patients with varying cataract severity, each vignette being presented twice in a randomised order (total vignette presentations = 300). The accuracy of opacity and management decisions were evaluated using descriptive statistics and non‐parametric Bland–Altman analysis where assessments from experienced clinicians were the reference. The precision of assessments was examined for each vignette form using non‐parametric Bland–Altman analysis. Results: All (n = 50) participants completed the study, with 36 working in primary eyecare (primary eyecare) settings and 14 in hospital eyecare services (HES). Agreement was highest where vignettes contained all clinical data (i.e., SL, OCT and visual function data—grading: 51.0%, management: 50.5%), and systematically reduced with decreasing vignette content (p < 0.001). A larger number of vignettes containing imaging and visual function measures exhibited below reference (i.e., less conservative) grading compared with vignettes containing imaging data alone (all p < 0.05). HES‐based optometrists were more likely to grade lens opacities lower than clinicians working in primary eyecare (p < 0.001). Good measurement precision was evident for all vignettes, with a mean bias close to zero and limits of agreement below one grading step for all conditions. Conclusions: The addition of anterior segment OCT to SL images improved the accuracy of lens opacity grading. Structural assessment alone yielded more conservative decision making, which reversed once visual functional data was available. [ABSTRACT FROM AUTHOR]

This series of six articles is inspired by themes arising from the Royal College of Midwives' state of midwifery education report. The series explores the current landscape and challenges in educating the future midwifery workforce, particularly those that relate to the higher education workforce. This penultimate article examines the interplay between the practice and academic environments and the impact this has on both students and staff alike, particularly in the wake of changing standards for student supervision. The article explores whether the nature of being an educator in a health field such as midwifery is unique because of the need to support students through placement challenges when there are limitations on what higher education institutions can realistically influence. It also examines the 'extra' responsibilities put on midwifery education staff to support students by way of 'academic assessor' roles. [ABSTRACT FROM AUTHOR]

Gateway science courses are an ongoing obstacle to recruitment into STEM fields (Science, Technology, Engineering, and Mathematics). Students come into courses that have a high cognitive load, which makes success in the course challenging. Instructional design can be used to reduce cognitive load. The findings demonstrate that leveraging pre- and post-lecture quizzes has the capacity to reduce cognitive load. Over three semesters, assessed 164 students were assessed while taking SCB201 (General Biology I). Students in the participant and control groups were given surveys to gauge the experiment's effectiveness. These surveys were given at the beginning, midterm, and end of the semester. The surveys collected student feedback concerning attendance habits, reading for knowledge, and course difficulty each semester. The participant group findings showed favorable increases in attendance and reading for knowledge. Additionally, students in the participant group found the quizzes helped them to better understand core concepts as the semester progressed. It was determined that these quizzes helped focus learning by causing a decrease in cognitive load for students. This methodology has universal application to any type of course needing to reduce cognitive load. [ABSTRACT FROM AUTHOR]

Different data types often occur in psychological and educational measurement such as computer‐based assessments that record performance and process data (e.g., response times and the number of actions). Modelling such data requires specific models for each data type and accommodating complex dependencies between multiple variables. Generalized linear latent variable models are suitable for modelling mixed data simultaneously, but estimation can be computationally demanding. A fast solution is to use Laplace approximations, but existing implementations of joint modelling of mixed data types are limited to ordinal and continuous data. To address this limitation, we derive an efficient estimation method that uses first‐ or second‐order Laplace approximations to simultaneously model ordinal data, continuous data, and count data. We illustrate the approach with an example and conduct simulations to evaluate the performance of the method in terms of estimation efficiency, convergence, and parameter recovery. The results suggest that the second‐order Laplace approximation achieves a higher convergence rate and produces accurate yet fast parameter estimates compared to the first‐order Laplace approximation, while the time cost increases with higher model complexity. Additionally, models that consider the dependence of variables from the same stimulus fit the empirical data substantially better than models that disregarded the dependence. [ABSTRACT FROM AUTHOR]

The article discusses the "US News and World Report" (USNWR) rankings in public health graduate education. Topics include argument of institutions on the methodology used for USNWR rankings, the growth in interest in public health as a profession during the COVID-19 pandemic, and options that would provide better data for promoting student fit for public health programs than rankings.

Background: This article is the last of a four-part series to guide educators on the construction and evaluation of multiple-choice test items in the post-licensure environment. Previous articles in this series described the problem and the mechanics of test item construction and evaluation. Method: A replicable strategy for evaluating the organizational process for constructing multiple-choice test questions is provided. Steps taken to create change are described; work tools are provided. Results: Guidance and training are needed to create multiple-choice test questions. Many educators have not had training in item construction. Educators welcomed training. Personalized mentorship resulted in improvement. Asynchronous learning alone was helpful and well received and improved self-perceived knowledge, yet fell short of achieving competence. Conclusion: Voluntary training may not be adequate to assure enculturation of best practices without accountability standards and monitoring. Future research is indicated to assess the situation and provide national standards for adoption within health care organizations. [J Contin Educ Nurs. 2024;55(11):535–542.] [ABSTRACT FROM AUTHOR]

Primary visual cortex (V1) has been the focus of extensive neurophysiological investigations, with its laminar organization serving as a crucial model for understanding the functional logic of neocortical microcircuits. Utilizing newly developed highdensity, Neuropixels probes, we measured visual responses from large populations of simultaneously recorded neurons distributed across layers of macaque V1. Within single recordings, myriad differences in the functional properties of neuronal subpopulations could be observed. Notably, while standard measurements of orientation selectivity showed only minor differences between laminar compartments, decoding stimulus orientation from layer 4C responses outperformed both superficial and deep layers within the same cortical column. The superior orientation discrimination within layer 4C was associated with greater response reliability of individual neurons rather than lower correlated activity within neuronal populations. Our results underscore the efficacy of high-density electrophysiology in revealing the functional organization and network properties of neocortical microcircuits within single experiments. [ABSTRACT FROM AUTHOR]

Background: Nursing aims to rely on the best evidence, yet nurses frequently struggle with statistics, impeding the integration of research into practice. The misuse of statistical significance and p values is a pervasive issue, widely debated across disciplines but often overlooked in nursing. Objective: This study seeks to elucidate key arguments surrounding the misuse of p values, assess their relevance to nursing, and propose recommendations for improvement. Approach: Conducting a critical literature review on the interpretation and reporting of statistical significance and its practical implications among nurses, nursing students, and scholars. Results: The literature reveals widespread misunderstandings of probability concepts in classical statistics, leading to the misuse of p values. Some scholars propose abandoning p values altogether due to these challenges. Rather than dismissing p values, this article provides insights into their historical context and proper application. Recommendations are offered for accurately interpreting results and integrating supplementary metrics. Fostering statistical competencies already at the undergraduate level can enhance statistical literacy and alleviate statistics anxiety among nursing students, a prevalent issue. Early exposure to statistical methods in nursing education empowers nurses to actively engage in research. Additional recommendations include preregistering analysis plans to mitigate publication bias and exploring alternative approaches such as Bayesian methods. Conclusions: While p values serve as a valuable tool for preliminary assessment against randomness in nursing research, their widespread misunderstanding necessitates multiple measures for accurate interpretation and understanding of statistical significance. It is imperative for nurse educators and researchers to incorporate these recommendations into their practices. [ABSTRACT FROM AUTHOR]

Introduction: The ability to self-assess is a crucial skill in identifying one's own strengths and weaknesses and in coordinating self-directed learning. The Dunning-Kruger effect occurs when limited knowledge causes individuals to overestimate their competence and underestimate others', leading to poor self-assessment and unrecognized incompetence. To serve as a foundation for developing strategies to improve self-assessment, the self-assessment abilities of first-semester students were assessed. Methods: In the final weeks of the summer 2021, winter 2021/22, and summer 2022 semesters, the academic performance (oral anatomy exam) of first semester students was assessed (0–15 points). Before the exam results were announced, students were asked to self-assess their performance. Results: Exam scores (M = 10.64, SD = 2.95) and self-assessed scores (M = 10.38, SD = 2.54) were comparable. The absolute difference between them, as a measure of self-assessment ability ranged from − 9 to + 9 points (M = -0.26, SD = 2.59). Among participants (N = 426), 18.5% assessed themselves accurately, 35.5% overestimated, and 46.0% underestimated their performance. The correlation between actual score and self-assessment was ρ = -0.590 (p < 0.001), reflecting the Dunning-Kruger effect. When separated by gender, correlation for females was ρ = -0.591 (p < 0.001), and for males ρ = -0.580 (p < 0.001). Conclusions: Realistic self-assessment is a challenge for first-semester students. The data indicate that females tend to overestimate their performance while males underestimate theirs. A pronounced Dunning-Kruger effect is evident in both genders, with significant negative correlations between self-assessment and actual performance. There are several reasons for the occurrence of the Dunning-Kruger effect. Considering that the COVID-19 pandemic influenced learning environments, collaborative learning was significantly restricted. The lack of opportunities for comparison could potentially lead to unrealistic self-assessment. [ABSTRACT FROM AUTHOR]

Background: Generalizability theory is widely used in psychological and educational measurement. Budget and cost are the problems that cannot be neglected in the measurement. When there is a budget constraint, the generalizability theory needs to consider how to design a measurement program with relatively high reliability and feasibility, which requires the optimal sample size to be estimated by some means. Lagrange multiplier method is a commonly used method for estimating the optimal sample size under budget constraints in generalizability theory. Unfortunately, to date, many formulas of estimating the optimal sample size for some more complex generalizability designs such as those with four facets or more facets have not been derived using the Lagrange multiplier method. Purpose: The purpose of this article is to provide a detailed step-by-step derivation of the formula of estimating the optimal sample size for three typical complex generalizability designs using the Lagrange multiplier method under budget constraints in generalizability theory, which can demonstrate the new roles of the Lagrange multiplier method. Method: This article derived the optimal sample size for teaching ability evaluation of college teachers with budget constraints in three generalizability designs such as the (s:t)×i, (s:t)× (i:v) and (s:t) × (i:v) ×o and explored their practical applications. By estimating the optimal sample size, the optimal generalizability design, which is more applicable in practice, can be compared to obtain. Findings: (1) Using the Lagrange multiplier method, the optimal sample size for students and items under budget constraints in different generalizability design can be derived. (2) For an example, based on teaching ability evaluation of college teachers in China, these designs of (s:t) ×i, (s:t) × (i:v) and (s:t) × (i:v) ×o were used to obtain the optimal sample size, which indicates the Lagrange multiplier method can been used in practice. (3) Under budget constraints, the (s:t) × (i:v) is the optimal generalizability design. The optimal sample size of students is 17 for each teacher and the optimal sample size of items is 4 for each dimension. Conclusion: The optimal sample size can be derived carefully using the Lagrange multiplier method under budget constraints in generalizability theory. The Lagrange multiplier method with new roles is worth recommending. [ABSTRACT FROM AUTHOR]

Normal ogive (NO) models have contributed substantially to the advancement of item response theory (IRT) and have become popular educational and psychological measurement models. However, estimating NO models remains computationally challenging. The purpose of this paper is to propose an efficient and reliable computational method for fitting NO models. Specifically, we introduce a novel and unified expectation‐maximization (EM) algorithm for estimating NO models, including two‐parameter, three‐parameter, and four‐parameter NO models. A key improvement in our EM algorithm lies in augmenting the NO model to be a complete data model within the exponential family, thereby substantially streamlining the implementation of the EM iteration and avoiding the numerical optimization computation in the M‐step. Additionally, we propose a two‐step expectation procedure for implementing the E‐step, which reduces the dimensionality of the integration and effectively enables numerical integration. Moreover, we develop a computing procedure for estimating the standard errors (SEs) of the estimated parameters. Simulation results demonstrate the superior performance of our algorithm in terms of its recovery accuracy, robustness, and computational efficiency. To further validate our methods, we apply them to real data from the Programme for International Student Assessment (PISA). The results affirm the reliability of the parameter estimates obtained using our method. [ABSTRACT FROM AUTHOR]

Primary visual cortex (V1) has been the focus of extensive neurophysiological investigations, with its laminar organization serving as a crucial model for understanding the functional logic of neocortical microcircuits. Utilizing newly developed highdensity, Neuropixels probes, we measured visual responses from large populations of simultaneously recorded neurons distributed across layers of macaque V1. Within single recordings, myriad differences in the functional properties of neuronal subpopulations could be observed. Notably, while standard measurements of orientation selectivity showed only minor differences between laminar compartments, decoding stimulus orientation from layer 4C responses outperformed both superficial and deep layers within the same cortical column. The superior orientation discrimination within layer 4C was associated with greater response reliability of individual neurons rather than lower correlated activity within neuronal populations. Our results underscore the efficacy of high-density electrophysiology in revealing the functional organization and network properties of neocortical microcircuits within single experiments. [ABSTRACT FROM AUTHOR]

Background: Online exams have become a more common form of assessment at universities due to the Covid‐19 pandemic. However, cheating behaviour in online exams is widespread and threatens exam validity as well as student learning and well‐being. Objective: To better understand the role of university students' needs, conceptions and reasons regarding cheating in online exams. Methods: In Study 1, we used four pairs of contrasting online exam scenarios to explore the impact of addressing students' needs on their cheating intention. In Study 2, we examined how students' conceptions of online exams are related to their cheating behaviour. In Study 3, we asked students to name their most important reasons for and against cheating in past online exams. All studies were conducted online and are based on a convenience sample of 339 students from universities in Germany. Results and Conclusions: First, students were less likely to cheat when they expected exam content relevant to their future profession, exam tasks relevant to their future professional life and detailed feedback on their performance. Second, most students' conceptions of online exams were related to their cheating intention and behaviour, whereas the conceptions that online exams support teaching, promote collaboration and impair learning were of relatively high importance. Third, most important reasons for cheating included the relevance of grades and the unfairness of exams, and most important reasons against cheating included moral standards and values as well as the fear of consequences. Implications: Addressing students' needs and considering their conceptions and reasons could be a learner‐centred approach to decrease cheating behaviour. Lay Description: What is currently known about this topic?: Online exams have become a more common form of assessment at universities.Cheating in online exams is a serious threat to the validity of exams.Technical approaches can reduce cheating but also students' well‐being. What does this paper add?: A learner‐centered approach can also reduce cheating in online exams.Insights into students' needs, conceptions, and reasons relevant to reducing cheating. Implications for practice: Using more relevant exam content, practically relevant exam tasks, and detailed feedback can reduce students' cheating intention.Knowing and discussing students' conceptions and reasons regarding cheating could improve learning and teaching and mitigate cheating. [ABSTRACT FROM AUTHOR]