Background: Distractor efficiency (DE) of multiple-choice questions (MCQs) responses is a component of the psychometric analysis used by the examiners to evaluate the distractors’ credibility and functionality. This study was conducted to evaluate the impact of the DE on the difficulty and discrimination indices. Methods: This cross-sectional study was conducted from April to June 2023. It utilizes the final exam of the Principles of Diseases Course with 45 s-year students. The exam consisted of 60 type A MCQs. Item analysis (IA) was generated to evaluate KR20, difficulty index (DIF), discrimination index (DIS), and distractor efficiency (DE). DIF was calculated as the percentage of examinees who scored the item correctly. DIS is an item’s ability to discriminate between higher and lower 27% of examinees. For DE, any distractor selected by less than 5% is considered nonfunctional, and items were classified according to the non-functional distractors. The correlation and significance of variance between DIF, DI, and DE were evaluated. Results: The total number of examinees was 45. The KR-20 of the exam was 0.91. The mean (M), and standard deviation (SD) of the DIF of the exam was 37.5(19.1), and the majority (69.5%) were of acceptable difficulty. The M (SD) of the DIS was 0.46 (0.22), which is excellent. Most items were excellent in discrimination (69.5%), only two were not discriminating (13.6%), and the rest were of acceptable power (16.9%). Items with excellent and good efficiency represent 37.3% each, while only 3.4% were of poor efficiency. The correlation between DE and DIF (p = 0.000, r= -0.548) indicates that items with efficient distractors (low number of NFD) are associated with those having a low difficulty index (difficult items) and vice versa. The correlation between DE and DIS is significantly negative (P = 0.0476, r=-0.259). In such a correlation, items with efficient distractors are associated with low-discriminating items. Conclusions: There is a significant moderate negative correlation between DE and DIF (P = 0.00, r = -0.548) and a significant weak negative correlation between DE and DIS (P = 0.0476, r = -0.259). DIF has a non-significant negative correlation with DIS (P = 0.7124, r = -0.0492). DE impacts both DIF and DIS. Items with efficient distractors (low number of NFD) are associated with those having a low difficulty index (difficult items) and discriminating items. Improving the quality of DE will decrease the number of NFDs and result in items with acceptable levels of difficulty index and discrimination power.

Background: The introduction of competency-based education models, student centers, and the increased use of formative assessments have led to demands for high-quality test items to be used in assessments. This study aimed to assess the use of an AI tool to generate MCQs type A and evaluate its quality. Methods: The study design was cross-sectional analytics conducted from June 2023 to August 2023. This study utilized formative TBL. The AI tool (ChatPdf.com) was selected to generate MCQs type A. The generated items were evaluated using a questionnaire for subject experts and an item (psychometric) analysis. The questionnaire to the subject experts about items was formed based on item quality and rating of item difficulty. Results: The total number of recurrent staff members as experts was 25, and the questionnaire response rate was 68%. The quality of the items ranged from good to excellent. None of the items had scenarios or vignettes and were direct. According to the expert’s rating, easy items represented 80%, and only two had moderate difficulty (20%). Only one item out of the two moderate difficulties had the same difficulty index. The total number of students participating in TBL was 48. The mean mark was 4.8 ± 1.7 out of 10. The KR20 is 0.68. Most items were of moderately difficult (90%) and only one was difficult (10%). The discrimination index of the items ranged from 0.77 to 0.15. Items with excellent discrimination represented 50% (5), items with good discrimination were 3 (30%), and only one time was poor (10%), and one was none discriminating. The non-functional distractors were 26 (86.7%), and the number of non-functional distractors was four (13.3%). According to distractor analysis, 60% of the items were excellent, and 40% were good. A significant correlation (p = 0.4, r = 0.30) was found between the difficulty and discrimination indices. Conclusion: Items constructed using AI had good psychometric properties and quality, measuring higher-order domains. AI allows the construction of many items within a short time. We hope this paper brings the use of AI in item generation and the associated challenges into a multi-layered discussion that will eventually lead to improvements in item generation and assessment in general.

Objectives: This research aims to describe the learning styles among undergraduate medical students at the College of Medicine, University of Bisha. Materials and methods: Type of study is a cross-sectional. Students preference of learning styles was assessed through VARK (abbreviation stands for Visual, Aural, Read/Write, and Kinesthetic learning style) inventory questionnaire version 7.1. The questionnaire was bilingually translated. Data from the questionnaire were analyzed by SPSS (V20). Data were presented in the form of descriptive statistics. One-way ANOVA and Kruskal–Wallis test were used to assess the relations between study variables. Results: One hundred and eighteen students (86.8%) were unimodal in their learning preference, and 18 students (13.3%) were multimodal. The dominant unimodal style was aural (55.9%), and the lowest was reading (5.1%). Among multimodal the commonest preference was AK (77.8%) followed by VR and VK equally (11.1%). The multimodal pattern is limited to students in level one. Visual style increases in percentage with the academic levels. Conclusion: Students in the College of Medicine, University of Bisha (UBCOM) have different patterns and types of learning style. Aural is the dominant unimodal style. The visual style is widely distributed among students of different levels. Planning and implementation of educational activities that satisfy all learning styles will support the learning process.

In the field of medical education, Item analysis is a statistical analysis of student’s responses on exam items and the relationship between them. It provides constructive feedback about items quality, increases the effectiveness of the exam, and supports exam validity and reliability. The decision of adding or removing an item should depends mainly on the result of the item analysis. The feedback of item analysis can support modification of instruction methods. This chapter provides a comprehensive review of item analysis (psychometric analysis) and also can be used as methodological guidance to perform an informative analysis. The chapter discusses item analysis under the following headings, importance of item analysis, factors affecting item analysis, parameters of item analysis and application. The parameters of item analysis includes the indices of the internal consistency, difficulty, discrimination, and distractor analysis.

The liver is central to metabolic, detoxification, and homeostatic functions. Exposure to hypobaric hypoxia at high altitudes causes detrimental effects on the liver, leading to injury. This study evaluated the effect of hypoxia-induced at high altitudes on liver function, oxidative stress, and histopathological changes in rats. This study used 24 male Wistar rats (aged 8–10 weeks). The hypoxia (hypobaric hypoxia) was inducted at a high altitude of 2,100 m above sea level. Normoxia is defined as 40 m above the sea level. The rats were randomly divided into two groups: a control group maintained at low altitudes and an experimental group exposed to high altitudes for eight weeks. Blood samples were collected from all rats through a cardiac puncture, and liver samples were taken through an abdominal approach. All samples were processed through standard methods and evaluated for liver function tests and histopathological assessment. Serum aspartate aminotransferase and alanine transaminase levels significantly increased by 25% and 30%, respectively, in the high-altitude group compared to controls (p < 0.01), indicating mild hepatocellular damage. Oxidative stress assessment indicated a significant elevation in malondialdehyde by 42% in the liver homogenates of high-altitude rats compared to controls (p < 0.001). Moreover, Superoxide dismutase activity and glutathione content decreased by 18% and 22% in the high-altitude group (p < 0.01), confirming the increased oxidative stress. Histologically, minimal inflammatory infiltration was observed in the rat livers at high altitudes, with no signs of necrosis or severe structural changes. Subclinical liver dysfunction, as evidenced by altered serum enzyme levels and increased oxidative stress with mild histological changes, is induced by high-altitude hypoxia in rats. This study’s results support that a hypobaric hypoxic environment physiologically stresses the liver. Further research into the long-term implications of hypobaric hypoxia and the adaptive responses of the liver is warranted.