Including general options on items, such as None-of-the-above (NOTA), could lead to worse psychometric properties. Further, personality traits are related to academic performance and could influence NOTA effects. Therefore, this study aims to test the effects of NOTA by manipulating its appearance and its use as the correct option or as a distractor, while considering the examinees' personality traits. The sample consisted of 449 psychology students who answered a statistics concept inventory. A crossed random-effects model was conducted to model the probability of answering an item correctly depending on items and students' covariates. The appearance of NOTA negatively affects the probability of answering correctly and changes between examinees. Conscientiousness, Extraversion, Emotional Stability, and previous knowledge of statistics are also significant predictors. The results point to increased items' difficulty when NOTA is included, although not all the examinees seem to show the same behavior when dealing with NOTA options.

Immunology education faces persistent challenges, including abstract concepts, theory-practice disconnect, and delayed feedback. Generative AI offers opportunities, yet its integration into pedagogical frameworks remains underexplored. We developed an Iterative AI-Augmented Immunology Education (IAIE) model integrating generative AI with the 4C/ID model and cognitive load theory. A 12-week quasi-experimental study enrolled 177 medical undergraduates (experimental: n = 88; control: n = 89), with outcomes assessed using the Host-Pathogen Interactions Concept Inventory (HPI-CI) and a modified Clinical Decision-Making in Nursing Scale (CDMNS). The experimental group showed significantly greater knowledge mastery (82.7 vs. 70.1, Cohen's d =1.12) and clinical decision-making accuracy (+31.7%). Over 84% of students recognized AI's value in understanding complex mechanisms. Reflective practice scores indicated high levels of reflective ability, and DREEM assessments confirmed strong student acceptance of the learning environment. The IAIE model effectively bridges theory and practice through AI-driven scaffolding that modulates cognitive load, fostering higher-order thinking and critical engagement with AI-generated content. This theory-informed framework offers a transferable approach for competency-based medical education.

Genomic literacy in nursing education: A systematic review of current knowledge, barriers, and integration.

Since most physiology core concepts are equally applicable to humans and other multicellular organisms, human physiology instructors may reasonably wonder whether consistent use of nonhuman assessment questions would enhance students' understanding of human biology, perhaps by offering novel contexts that demand application of human physiology concepts. In this study, we explore this by comparing two types of assessments: test banks from human physiology textbooks and vetted assessments prioritizing physiology core concept knowledge. We checked for nonhuman questions and further categorized each nonhuman example as having No Analogy or Perfect Analogy or Uncertain Analogy to humans, with the latter having potential for assessment of higher-order cognitive skills (HOCS). We found that of nearly 14,000 test bank questions from 6 different human physiology textbooks, only 53 concerned nonhumans, and only 6 of those were judged to be Uncertain Analogy. Practice Medical College Admission Test (MCAT) exams and physiology concept inventories included nonhuman questions at rates ranging from 11% to 80%. We further classified the nonhuman questions (n = 164) from all sources as assessing lower-order cognitive skills (LOCS) or HOCS and found that on average the Uncertain Analogy bin (n = 67) had the highest average percentage of HOCS questions at 61.6%. Our data suggest a mismatch between the potentially high value of nonhuman questions for HOCS development and their rarity in test banks, and we recommend greater inclusion of nonhuman questions in test banks. For instructors interested in using nonhuman examples in assessments, Test Question Templates (TQTs), which help generate questions based on lesson learning objectives, may be useful.NEW & NOTEWORTHY This study analyzed human physiology textbook test banks and vetted physiology assessments for nonhuman questions that might challenge students to apply human physiology concepts in novel scenarios. We found that test banks had a far lower proportion of nonhuman questions compared with Medical College Admission Test (MCAT) practice tests and physiology concept inventories. We recommend nonhuman questions in human physiology assessments to enhance higher-order cognition about physiology core concepts and recommend using TQTs to generate such novel questions.

Advancements in artificial intelligence (AI) make AI literacy essential. However, non-specialist university students often hold misunderstandings of basic AI concepts. This study used a mixed-methods approach to identify which AI concepts are most challenging for novice learners in a college population. Using the Artificial Intelligence Literacy Concept Inventory (AI-CI) and a confirmatory multidimensional Item Response Theory (MIRT) analysis, we found that items in the AI-CI “Machine Learning (ML)” dimension (i.e., a dimension focused on general ML ideas such as learning from data and distinguishing supervised vs. unsupervised learning) were more difficult for participants than items in the other AI-CI dimensions (i.e., What is AI, Decision Trees, Supervised Learning, Generative Adversarial Networks, and Neural Networks). Cognitive interviews further suggested that everyday knowledge supported interpretation of several AI concepts, but many ML items required more technical mental models (e.g., how training data relates to prediction and generalization). These findings highlight prevalent ML-related misconceptions among the students in our study and suggest the need for targeted instruction that explicitly addresses learning-from-data, labeling, and generalization in higher education AI literacy contexts.

Misconceptions in pharmacology can undermine learning and compromise both clinical and scientific reasoning, yet few validated tools exist to identify them. Consequently, we developed and validated the Pharmacology Concept Inventory (PCI), which can be used to identify misconceptions, assess learning gains, and evaluate teaching effectiveness. This PCI was designed based on the IUPHAR-Education Section (IUPHAR-Ed) Core Concepts of Pharmacology Project, addressing eight core concepts: drug efficacy, drug-target interaction, steady-state concentration, structure-activity relationship, drug tolerance, drug bioavailability, volume of distribution, and drug clearance. A triangulated design strategy integrated theoretical frameworks, expert review, and student perspectives. Experts examined quality, content validity, and cognitive alignment. The pilot PCI was then administered to a student cohort to evaluate its psychometric properties, providing preliminary evidence for further refinement. Item-level content validity indices ranged from 0.67 to 1.00, with a scale-level average of 0.93. Seventy students completed the pilot survey, leading to the exclusion of items with low discrimination and reliability. Items on drug-target interaction were removed due to consistently poor performance. The final PCI included 26 items covering seven concepts, with strong discrimination indices (0.36-0.75) and difficulty indices (0.26-0.71). Internal consistency was high (Cronbach's alpha = 0.91), and concept-level reliability ranged from 0.64 to 0.85. The PCI provides strong evidence for identifying misconceptions and assessing learning outcomes through a pre-post-test approach. Although the PCI currently addresses only a subset of concepts, continued refinements informed by surveys and interviews will enhance its utility and expand its scope for concept-based learning and curriculum evaluation.

A significant body of research has employed concept inventories to diagnose students’ conceptual understanding in physics. However, there remains limited evidence on their effectiveness in secondary school contexts in Sub-Saharan Africa and on whether advanced item-level analyses can reveal persistent misconceptions. This study examines the application of the Circular Motion Concept Inventory (CMCI) to evaluate learning progress and identify misconceptions among Ugandan secondary school physics students. Using a pre–post-test design, the CMCI was administered to 198 Advanced Level physics students both before and after a structured instructional intervention that incorporated physical models, diagrams, graphs, charts, and illustrations. Data were analysed using descriptive statistics, Classical Test Theory (CTT), and Item Response Curves (IRCs) to assess normalized learning gain, item-based indices, and misconception patterns across different ability levels. Results indicate a moderate improvement in conceptual understanding, with mean scores increasing from 6.61 on the pre-test to 10.03 on the post-test, and average item difficulty rising to 0.50. Despite these gains, IRCs analyses revealed persistent misconceptions related to centripetal force, acceleration direction, and motion on banked curves, particularly among low-ability students. Think-aloud interviews supported these findings by exposing gaps in students’ conceptual reasoning even when correct answers were selected. The study demonstrates that IRC analysis provides diagnostic insights beyond conventional CTT measures by revealing how misconceptions persist across ability levels. These findings underscore the value of integrating CMCI and IRC-based analyses into instructional design to inform targeted, evidence-based interventions aimed at improving students’ conceptual understanding of circular motion.

The purpose of this study was to examine the impact of an intervention, a "CURE lecture" approach, that introduced course-based undergraduate research experience (CURE) strategies into the lecture setting. Rather than learning biological explanations from a traditional textbook, instead students studied primary literature curated in a reformed research-focused textbook and had discussions of data and experimental design. In control cohorts, reformed active and cooperative pedagogies were used in lecture to engage students in learning traditional textbook content. In experimental cohorts, "lecture" format was replaced with active and cooperative "journal club" discussions of published experiments. Prior studies examined use of research-focused Integrating Concepts in Biology (ICB) textbook readings in two sequential introductory biology courses. In this study, assessments focused on student learning gains after a single semester. Klymkowsky's Biology Concept Inventory with known misconceptions as distractors and Loznak's Medical College Admission Test (MCAT) instrument used for over a decade prior joined longitudinal tracking to evaluate impact of intervention. The ICB student cohort had higher scores (46.3% vs. 34.3%) than the control cohort on the concept inventory and on the MCAT questions performed comparably in the range achieved by peer control students since the year 2000. Longitudinal tracking revealed that ICB students immediately outperformed peers in their next biology course the following semester. The literature suggested that a two-semester ICB experience helped students better succeed, and these findings support that even a shorter exposure, of just a single semester, to the CURE lecture strategy is impactful to students.NEW & NOTEWORTHY A "CURE lecture" approach was used in physiology majors' first introductory biology course, where journal club strategies replaced lecture in class meetings. Rather than lectures on biological explanations from a traditional textbook, students constructed their knowledge via primary literature readings in a reformed textbook aided by discussions of data and experimental design. When assessed by a MCAT instrument, Biology Concept Inventory, and tracking student performance, the experimental student cohort outperformed the peer control cohort.

Preliminary Investigation of Validating Chain Computer Adaptive Testing Based on the Force Concept Inventory

The default mode network: A transmodal cortical system for enhancing cognition and sharing mental worlds in language-specific, culturally diverse ways.

Misconceptions in physics education continue to be a persistent challenge because they hinder meaningful learning, weaken conceptual understanding, and reduce students’ ability to accurately interpret physical phenomena. Although research on this topic has grown over the past decade, the literature remains fragmented across different educational levels, physics topics, diagnostic approaches, and remediation strategies. This study aimed to provide an updated and structured overview of influential research on misconceptions in physics by analyzing research trends, misconception profiles, diagnostic tools, and remediation techniques. A citation-based systematic mapping review was conducted using the Scopus database. The search was limited to English-language journal articles and conference proceedings published between 2015 and 2024, with the top 100 records ranked by citation count screened, resulting in 74 studies included in the final analysis. The results show that research on misconceptions in physics primarily focuses on university and high school students, with classical mechanics the most studied topic, followed by electricity, magnetism, and wave-related concepts. In terms of diagnosis, four-tier diagnostic tests were the most frequently used instruments, followed by established concept inventories such as the Force Concept Inventory. Concerning remediation, diagnostic-based interventions, conceptual change strategies, and cognitive conflict-based learning were the most prominent approaches. However, a significant number of studies did not explicitly identify the causes of misconceptions or report clear remediation strategies. The novelty of this review lies in its integrative mapping of influential studies across multiple analytical dimensions within a single physics-specific framework. This research contributes to physics education by offering a structured reference for future work on diagnostic development, causal analysis, and the design of more context-sensitive instructional interventions.

We utilize concepts of numeracy including number sense, reading and interpreting graphs, basic probability and statistics, and reasoning to estimate guessing and verify our earlier findings on human self-assessment as replicable. Our field study employed a low-stakes paired measures assessment (11,229 scores from the validated Science Literacy Concept Inventory and postdicted global self-assessment ratings generated upon completion of the Inventory) in conjunction with a five-category taxonomy of self-assessment proficiency. We also simulated 11,229 random guessing responses, to model responses that disengaged, purely random-guessing participants should produce. At least 90% of participants sincerely engaged with the instruments of measure, self-assessed imperfectly but reasonably well, and exhibited equal tendencies to underestimate or overestimate their scores by modest amounts. Results contradict the prevalent claim that most people overestimate their actual abilities, with the least knowledgeable being grossly overconfident (ie, the Dunning-Kruger effect). In this study, disengaged, random guessers could account for nearly all participants who grossly overestimated. Confirming that significant numbers of low-scoring participants are aware of their poor performance removes support from the "dual-burden hypothesis," which states that low-scoring participants lack both the competence and metacognitive competence needed for accurate self-assessment. The amount of guessing in a populace does not attenuate the "effect," as claimed in recent psychology literature, but magnifies it. Studies of paired measures yielded a new understanding of guessing. The "effect" is better explained as an illusion produced by probability than as an accurate portrayal of human self-assessment.

The Algebra Concept Inventory (ACI) is the first large-scale instrument validated to measure the foundational algebraic conceptual understanding of college students. This study uses ACI scores to conduct the first quantitative analysis on the relationship between algebraic conceptual understanding and college outcomes, thus exploring the predictive validity of the ACI. Specifically, we investigate whether ACI scores predict: (1) math course grades; (2) subsequent completion of math courses required for STEM (science, technology, engineering, and mathematics) majors; (3) completion of STEM versus non-STEM degrees; and (4) the extent that differences in these outcomes by race/ethnicity or gender are explained by ACI scores. Results indicate that ACI scores significantly predict math course outcomes and STEM versus non-STEM degree completion, as well as significant proportions of differences in these outcomes by race/ethnicity and gender. This illustrates the importance of providing every student instruction that supports development of the kinds of foundational algebraic conceptual understanding measured by the ACI.

This study examines how sustained conceptual instruction influences gender disparities in physics understanding among Swedish upper secondary students. Drawing on Ausubel’s Meaningful Learning Theory and Vergnaud’s Conceptual Field Theory, the research explores how instructional design interacts with students’ cognitive development, prior knowledge, and sociocultural context. Using a quasi-experimental design, 852 students from 38 classes were assessed using a gender-balanced version of the Force Concept Inventory (G-FCI). Normalized change was applied to measure conceptual gains across instructional methods and genders. Findings confirm persistent gender gaps under traditional instruction, favoring male students. However, in cohorts with sustained conceptual teaching across Physics 1 and 2, female students outperformed male peers—a statistically significant shift not observed under traditional methods. While conceptual instruction improved learning for all, its equity potential was most evident when implemented consistently. These results highlight the importance of pedagogical continuity for promoting gender equity in physics education. Nevertheless, instructional change alone is insufficient; broader interventions addressing classroom climate, stereotype threat, and identity development are needed. The study contributes empirical evidence to the international discourse on gender and science education and underscores the value of conceptually grounded pedagogy as part of a systemic strategy for equitable physics learning.

This theoretical essay aims to present and discuss the possibilities of using Model Analysis in educational research involving multiple-choice tests. This approach is based on the premise that such tests can reveal, in greater depth, students’ conceptions about scientific concepts. Based on a bibliographic investigation, the essay examines the application of Model Analysis in international studies and highlights its limited presence in national literature. The tool has proven to be promising in understanding students' thinking patterns, especially regarding non-scientific conceptions in topics such as Newton's Laws, which are frequently assessed by instruments like the Force Concept Inventory (FCI). By systematizing and disseminating the potential of this analytical tool, the study aims to contribute to the consolidation of more in-depth quantitative analyses in the field of science education research, particularly in Physics.

Background and Purpose: Genomic literacy is essential for nurses to integrate genomics into clinical practice. The Genomic Nursing Concept Inventory (GNCI) is a validated tool to assess genomic literacy. This study aimed to validate the Italian version of the GNCI (GNCIITA) and evaluate its psychometric properties. Methods: A cross-sectional study was conducted in March 2024 with 315 nursing students from an Italian university. The tool was translated following Beaton's guidelines, and data were collected via an online survey. Exploratory and confirmatory factor analyses assessed the factor structure. Internal consistency and reliability were evaluated using Cronbach's α and Spearman-Brown coefficient. Item difficulty and discrimination were also analyzed. Results: The analyses supported a one-factor solution, consistent with the original validation study. Item difficulty and internal consistency of both the full 31-item version and the shortened 20-item version aligned wih the original instrument. Conclusions: The GNCIITA is a reliable instrument for assessing genomic literacy in Italian nursing students.

Physics education research (PER) has shown substantial growth in recent years, yet comprehensive reviews mapping the field’s overall trajectory remain scarce. The leading journal, (PRPER), has been a cornerstone of the discipline since its launch in 2005. Marking its 20th anniversary, this study presents a comprehensive bibliometric analysis of PRPER publications from July 2005 to June 2025. Using data extracted from the Web of Science and Scopus, this study examines key indicators, including publication/citation trends, contributor demographics, prolific author characteristics, and collaborations, alongside the field’s intellectual structures and their evolution. The results reveal sustained growth in publication volume and a concentration of authorship within U.S.-based institutions. The analysis finds that PRPER publications group well into seven major research clusters: Understanding and Supporting Student Learning; Identity and Equity; Conceptual Inventory; Physics Laboratory; Physics Problem Solving; Attitude and Epistemology; and Quantum Physics Education. Notably, Quantum Physics Education emerges in this analysis as one of the seven distinct major research clusters identified through bibliographic coupling. Timeline analysis reveals a shift in thematic emphasis from foundational work on conceptual assessment toward increasing focus on identity, equity, and quantum education. This bibliometric overview not only traces the intellectual trajectory of PRPER but also offers insights into the broader evolution of PER, highlighting existing gaps, such as the need to integrate equity research into quantum education, and suggesting future directions for the field.

In this article, we report the development and validation of a new two-tier concept inventory, the Basic Electricity Assessment of Students’ Thinking (BEAST), designed to assess common conceptual difficulties (“student ideas,” such as current consumption and sequential reasoning) and the understanding of fundamental electric circuit concepts (e.g., current, voltage, and resistance) among undergraduate students. The final version of the BEAST covers six student ideas, each linked to a distinct physical concept. Each student idea is assessed using three two-tier single-choice items. To refine the items and evaluate their content validity, including the correctness of answers and the intended categorization of student ideas based on response patterns, feedback and ratings from five experts were incorporated. The test was administered to a sample of <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mi>N</a:mi> <a:mo>=</a:mo> <a:mn>176</a:mn> </a:math> students enrolled in introductory physics courses across six different German universities. Quantitative evaluation using classical test theory and structural analyses demonstrated strong evidence supporting the test’s content and construct validity. Confirmatory factor analysis utilizing parsimonious bifactor models showed a good fit of the model to the data.

The purpose of this study is to examine the self-reported knowledge, attitudes, and perceived barriers to the integration of genomic concepts into the nursing curriculum among nursing faculty in the United States. A cross-sectional descriptive correlational study using a convenience sample was conducted to survey 150 nursing faculty in the United States. Data were collected via Qualtrics using the Genomic Nursing Concept Inventory (GNCI), the Genetics and Genomics in Nursing Practice Survey (GGNPS), and a demographic data form. The mean score on the 31-item GNCI was 13.6, and the mean GGNPS 12-item knowledge score was 9.1. Age, educational preparation, and active clinical practice did not make a significant difference in the knowledge of the participants. Professional development, intentional enrollment in genomic-specific courses, and clear expectations can improve faculty knowledge, which can foster curricular integration.

This quantitative study examined whether teaching mode—flipped classroom (FC) versus traditional classroom (TC)—is associated with differences in high-school physics students perceived conceptual mastery (PCMS) and physics learning engagement (PLE). Using a cross-sectional, between-groups design, N = 298 students (FC n = 151; TC n = 147) completed brief Likert-type questionnaires (PCMS, 8 items; PLE, 8 items). Analyses were intentionally limited to descriptive statistics, independent-samples t tests, and one-way ANOVAs. Results showed that FC students reported significantly higher PCMS than TC students (ΔM = 0.22, t (296) = 3.21, p = .0015, d = 0.37) and higher PLE (ΔM = 0.29, t (296) = 4.83, p &lt; .001, d = 0.56). Grade-level ANOVAs revealed modest developmental trends favoring upper grades (PCMS: η² = .023; PLE: η² = .041). Findings suggest that flipped organization is associated with moderately higher engagement and modestly higher perceived conceptual understanding beyond grade effects. Pedagogically, the results support dedicating in-class time to structured problem solving, guided inquiry, and formative feedback while moving content exposure to pre-class micro-materials. Limitations include the cross-sectional design with intact classes, reliance on self-report outcomes, and the absence of covariate adjustment. Future research should combine perceptual measures with standardized concept inventories (e.g., FCI/CSEM) and process data, and test design features and carefully scaffolded AI augmentations as potential moderators. Keywords: flipped classroom; physics education; conceptual mastery; learning engagement; high school; independent-samples t test; one-way ANOVA DOI : 10.7176/JEP/16-13-04 Publication date : December 30th 2025