Test Preparation Research Articles

Influence of Teachers’ Experience in Information Communication Technology and Students’ Academic Performance in Mathematics in Public Secondary Schools of Rwanda: A Case of Kayonza District

The study evaluated the impact of teachers' ICT experience on students' math performance in public secondary schools in Kayonza District, Rwanda. Involving 259 participants (223 teachers and 36 head teachers), data were gathered through questionnaires, interviews, and observations, and analyzed using SPSS Version 20.0. Findings revealed that 83.5% of respondents strongly agreed that teachers skilled in MS Excel, 85.9% in PowerPoint, and 83.9% in preparing teaching materials with ICT tools positively influenced students' performance. Additionally, 82.3% noted that teachers trained in exam preparation with ICT tools demonstrated their ICT experience. Improved student outcomes were reported, with 79.4% noting better numeracy, 80.2% improved grades, and 78.3% enhanced skills in experimenting with MS Excel. A significant positive correlation was found between teachers' ICT expertise and students' math performance. The study suggests that proficiency in ICT tools enhances students' academic performance. The Ministry of Education should support ICT integration to boost academic achievement, with superintendents and head teachers optimizing ICT training and lab usage. Teachers should share ICT skills to improve instruction and student outcomes. Future research should investigate the broader effects of ICT in education on academic achievement in mathematics.

Performance evaluation of ChatGPT 4.0 on cardiovascular questions from the medical knowledge self-assessment program

Abstract Background Medical trainees are increasingly using online chat-based artificial intelligence (AI) platforms as supplementary resources for board exam preparation and clinical decision support. Prior studies have evaluated the performance of AI chatbots like ChatGPT on various general standardized tests such as the United States Medical Licensing Examination (USMLE), but little is known about their performance on subspecialty-focused exam questions, particularly related to clinical management and treatment. Objective This study aims to evaluate the performance of ChatGPT version 4.0 on the cardiovascular questions from the Medical Knowledge Self-Assessment Program (MKSAP) 19, a widely used resource for board exam preparation in the United States. Methods We submitted all cardiovascular questions from MKSAP 19 to ChatGPT 4.0, covering a broad range of cardiology topics in a multiple-choice format. Performance was gauged against both the official MKSAP answer key and average trainee scores obtained from the MKSAP website. Out of 129 questions, 4 were invalidated due to post-publication data, and 18 were excluded due to reliance on visual aids, leaving 107 questions for analysis. Results ChatGPT 4.0 correctly answered 93 out of 107 questions, reflecting an 87% accuracy rate, compared to a 60% accuracy rate averaged among all human users for the same questions (p<0.0001). ChatGPT accuracy rates for each question category (e.g., heart failure, electrophysiology, etc.) are provided in the figure. On the 14 questions that ChatGPT answered incorrectly, human users averaged a 47% accuracy rate. All 14 incorrectly answered questions were related to clinical management and treatment (as opposed to diagnosis or epidemiology), and the majority (10/14) involved choosing treatment medications or choosing between medications versus interventions. Conclusion ChatGPT 4.0 surpassed the typical 70% accuracy threshold required for passing the internal medicine board certification but performed less well in answering questions about clinical management and treatment. This performance suggests that ChatGPT 4.0 could be an effective adjunct tool for cardiology education, but raises some concerns about its use in clinical decision support for trainees.

Bioequivalence study of eltrombopag 75 mg film-coated tablets under fasting conditions during the Covid-19 pandemic in healthy Caucasian male subjects

This study aims to determine the bioequivalence of the reference preparation and the test preparation containing eltrombopag when both were given during the COVID-19 pandemic while fasting. Participants in the research were healthy male Caucasian subjects. One film-coated tablet of the test preparation or one film tablet of the reference preparation, equivalent to 75 mg of eltrombopag, was given to the participants in a randomized order throughout each treatment session. At pre determined blood sampling points, blood samples were taken to determine the pharmacokinetics of eltrombopag. Eltrombopag concentrations in the samples were determined using an LC-MS/MS technique verified using ESI(−). The study results were used to calculate the rate (the maximum plasma concentration, or Cmax) and extent (area under the concentration-time curve of plasma, or AUC(0−72) and AUC(0−t) of eltrombopag absorption from the test preparation and reference preparation. The 90% confidence intervals (CI) of the ln-transformed AUC(0−72), AUC(0−t), and Cmax of eltrombopag met the bioequivalence requirements of 80.00–125.00%. Both trial preparations had a similar and very satisfactory safety profile.

Evaluating the Performance of ChatGPT, Gemini, and Bing Compared with Resident Surgeons in the Otorhinolaryngology In-service Training Examination.

Large language models (LLMs) are used in various fields for their ability to produce human-like text. They are particularly useful in medical education, aiding clinical management skills and exam preparation for residents. To evaluate and compare the performance of ChatGPT (GPT-4), Gemini, and Bing with each other and with otorhinolaryngology residents in answering in-service training exam questions and provide insights into the usefulness of these models in medical education and healthcare. Eight otorhinolaryngology in-service training exams were used for comparison. 316 questions were prepared from the Resident Training Textbook of the Turkish Society of Otorhinolaryngology Head and Neck Surgery. These questions were presented to the three artificial intelligence models. The exam results were evaluated to determine the accuracy of both models and residents. GPT-4 achieved the highest accuracy among the LLMs at 54.75% (GPT-4 vs. Gemini p=0.002, GPT-4 vs. Bing p<0.001), followed by Gemini at 40.50% and Bing at 37.00% (Gemini vs. Bing p=0.327). However, senior residents outperformed all LLMs and other residents with an accuracy rate of 75.5% (p<0.001). The LLMs could only compete with junior residents. GPT- 4 and Gemini performed similarly to juniors, whose accuracy level was 46.90% (p=0.058 and p=0.120, respectively). However, juniors still outperformed Bing (p=0.019). The LLMs currently have limitations in achieving the same medical accuracy as senior and mid-level residents. However, they outperform in specific subspecialties, indicating the potential usefulness in certain medical fields.

A Bioequivalence Study of Azilsartan in Healthy Chinese Subjects.

Azilsartan is an angiotensin II receptor blocker used for treating adult hypertension. It significantly improves cardiovascular outcomes in patients with high-risk hypertension, heart failure, and diabetic nephropathy. A single-center, randomized, open-label, single-dose, dual-cycle, dual-crossover clinical trial was conducted to evaluate the bioequivalence of azilsartan under fasting and postprandial conditions in 60 Chinese healthy volunteers. Thirty healthy subjects were enrolled in each test group, with random cross-administration for fasting and postprandial tests. The concentration of azilsartan in human plasma was evaluated using liquid chromatography-tandem mass spectrometry after a single oral administration of test and reference preparations, each at a dose of 20mg (1 tablet). Pharmacokinetic parameters were determined using WinNonlin8.2 software, and bioequivalence was evaluated using SAS 9.4 software. The geometric mean ratios and 90% confidence intervals for maximum concentration, area under the plasma concentration-time curve from time 0 to the time of last measurable concentration, and area under the plasma concentration-time curve from time 0 to infinity of the test and reference preparations in the fasting and postprandial test groups were in the range of 80%-125%. The incidence of adverse events in the fasting and postprandial test groups was 30% (9/30) and 33.3% (10/30), respectively. No serious adverse events or unexpected adverse drug reactions were observed. In conclusion, the test and reference preparations of azilsartan tablets demonstrate bioequivalence and good safety in healthy Chinese subjects under fasting and postprandial conditions.

Bioequivalence Analysis of Clindamycin Hydrochloride Capsules in Healthy Chinese Subjects Under Fasted and Fed Conditions.

Clindamycin is a lincosamide antibiotic for the treatment of staphylococcal, streptococcal, and anaerobic bacterial infections. We conducted a single-center, single-dose, 2-preparation, 2-period, 2-sequence, randomized, open-label, 2×2 crossover study to evaluate the pharmacokinetics (PKs) and safety of the test and reference clindamycin hydrochloride capsules in healthy Chinese subjects under both fasted and fed conditions. Forty-eight subjects were enrolled in the study totally, with 24 subjects in each group. All subjects were asked to take a test or reference preparation, under either fasted or fed condition, and their blood samples were collected and assayed by a validated high-performance liquid chromatography-tandem mass spectrometry method. PK parameters including maximum plasma concentration, area under the plasma concentration-time curve from time 0 to the last concentration, and area under the plasma concentration-time curve from time 0 to infinity were estimated with noncompartmental model and analyzed. Results showed that the PK profiles of the 2 preparations were consistent and met the bioequivalence criteria. Food was identified as a factor that had an impact on clindamycin absorption. The safety of clindamycin hydrochloride capsules was satisfactory. This study proved that the 2 clindamycin hydrochloride capsules were bioequivalent in healthy Chinese subjects under both fasted and fed conditions.

Think Aloud Videos and Assessment in an Introductory Economics Class for Undergraduate Students

This paper demonstrates the value of an innovative test preparation strategy, applied over multiple semesters to one principles of macroeconomics class. The professor makes a video of himself taking a copy of the test students are preparing for, talking aloud about how to think about the question and work through the solution. A natural experiment occurred one semester when the professor was unable to provide the think-aloud preparation video, but other, standard preparation materials were in place. It is demonstrated that students increase their scores on other questions in the same modules by an average of 7.6 percentage points with think-aloud videos. Think aloud interventions are shown to be an effective tool to enhance student content learning.

대학 비교과 프로그램 특성에 따른 학생 학습경험 분석: 경북 소재 대학의 비교과 프로그램에 대한 분석을 중심으로

Objectives This study conducted keyword network analysis to examine student experiences based on the characteristics of extracurricular programs at universities. The aim is to understand how these programs impact students' learning experiences. Methods Keyword network analysis was used based on keywords extracted from various survey contents. The NodeXL program was used to visualize the main keywords and their relationships for each type of extracurricular program (mentoring, tutoring, experiential). Results In mentoring programs, keywords such as ‘feedback’, ‘support’, and ‘adaptation’ were central, indicating that students enhance their self-directed learning and communication skills. In tutoring programs, keywords like ‘exam preparation’, ‘study strategies’, and ‘grade improvement’ were prominent, showing that students focus on academic achievement. In experiential programs, keywords such as ‘practice’, ‘experience’, and ‘projects’ stood out, highlighting a focus on practical learning. Conclusions The keyword network analysis revealed that students' learning experiences vary according to the characteristics of the extracurricular programs. These findings provide important insights for universities to design and operate extracurricular programs that meet the diverse learning needs of students.

Chinese English‐as‐a‐foreign‐language learners’ directed motivational currents for high‐stakes English exam preparation

AbstractA directed motivational current (DMC) is an intense motivational drive that sustains long‐term behavior toward a valued goal. The quantitative study investigated the DMCs of English‐as‐a‐foreign‐language learners and their predictive role on learning performance in a high‐stakes English exam preparation context. The DMC dimension scale was distributed to Chinese English‐as‐a‐foreign‐language learners who experienced the National Postgraduate Entrance Examination, and data from 323 participants were retained for analysis. Independent T‐tests, Analysis of Variance (ANOVA), and regression analyses were performed to report findings on DMC levels, and influencing factors and impacts of DMCs. Results suggest a high DMC level during exam preparation, with female learners showing more goal‐oriented salient facilitative structure, and clear perception of progress than males, while high‐proficiency learners demonstrated greater participant ownership and “perceived behavioral control” than medium‐ and low‐proficiency learners. No differences were found between learners majoring in humanities/social sciences and those studying science, technology, engineering, or mathematics. The five DMC dimensions collectively predicted English performance. Following self‐determination theory, the predictive role is explained. Theoretically, DMC components and their impacts on academic outcomes were reconfirmed in the Chinese English‐as‐a‐foreign‐language context; practically, educators and students are advised to use the DMC framework to enhance English performance in high‐stakes exam preparation.

Comprehensive review of resources and strategy for dermatology board certification exams in the United States.

This article offers an up-to-date overview of resources tailored for dermatology residents in the United States preparing for their board certification exams. We have assembled a comprehensive list of exam preparation resources categorized by cost, alongside recommendations from attending and resident physicians regarding the most effective resources for each exam. Although examinations are only one facet of the training involved in becoming a competent dermatologist, these exams help residents focus on learning crucial aspects of medicine. This review aims to furnish a concise summary of available resources for dermatology residents, organized by cost. The average cost of a paid dermatology question bank resource in this review was approximately $279, reflecting the need for review resources for board exam preparation that can fit a resident physician's budget or are free to use.

Using open online courses on programming in organizing independent work of students

The article highlights the need to use online courses on programming, including automatic code checking, in organizing independent work of high school students. An overview of open online courses designed to study the Python programming language, implemented on different platforms, is provided. The capabilities of each online course for solving educational problems, such as general training of students in programming, preparation for state exams, developing skills in solving Olympiad problems, organizing project activities, and career guidance for schoolchildren are discussed. The technical capabilities of the platforms on which the courses are presented are analyzed from the point of view of their didactic potential. Forms of organizing independent work of students using online courses on programming are proposed. The general algorithm for solving programming problems is specified taking into account the specifics of using the automatic system for checking and evaluating the solution implemented in online courses.

TRANSFORMATIVE PEDAGOGY IN THE DIGITAL AGE: UNRAVELING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON HIGHER EDUCATION STUDENTS

Artificial Intelligence (AI) has become a transformative force in education, significantly influencing students. This research explores AI's impact on learning experiences, academic performance, career guidance, motivation, self-reliance, social interaction, and AI dependency. Utilizing a descriptive-comparative design, 194 student respondents were chosen through stratified sampling. The results show that students generally perceive AI positively. Students agree that AI enhances personalized learning, engagement, and critical thinking, although practical hands-on learning experiences received less favorable feedback. Academically, students concur that AI helps them identify weaknesses, improve assignments, and track progress, despite some reservations about its efficacy in exam preparation. For career guidance, students agree that AI effectively matches skills with career options, recommends internships, and provides resources, though it is less effective for long-term planning. Students also believe AI boosts motivation through gamified learning and progress tracking and fosters self-reliance via self-directed learning and critical thinking support. Socially, students agree that AI facilitates collaboration, peer learning, and networking. Additionally, students demonstrate a reliance on AI for their learning processes. Notably, female students report a more significant impact on social interactions than male students. The type of device used (laptop vs. cellphone) significantly affects the learning experience, with laptop users reporting a more substantial impact. Differences in AI's impact are noted among various courses, particularly benefiting education students more than those in hospitality management and agriculture. However, age and family income do not significantly influence AI's overall impact. Keywords: Artificial Intelligence, descriptive-comparative, impact on learning, higher education

Enrollment to exams: Perceived stress dynamics among first-year physics students

The current dropout rate in physics studies in Germany is about 60%, with the majority of dropouts occurring in the first year. Consequently, the physics study entry phase poses a significant challenge for many students. Students’ stress perceptions can provide more profound insights into the processes and challenges during that period. In a panel study featuring 67 measuring points involving up to 128 participants at each point, we investigated students’ stress perceptions with the perceived stress questionnaire (PSQ), identified underlying sources of stress, and assessed self-estimated workloads across two different cohorts. This examination occurred almost every week during the first semester, and for one cohort also in the second semester, yielding a total of 3241 PSQ data points and 5823 stressors. The PSQ data indicate a consistent stress trajectory across all three groups studied that is characterized by significant dynamics between measuring points, spanning from M=20.1,SD=15.9 to M=63.6,SD=13.4 on a scale from 0 to 100. Stress levels rise in the first weeks of the lecture, followed by stable, elevated stress levels until the exams and a relaxation phase afterward during the lecture-free time and Christmas vacation. In the first half of the lecture period, students primarily indicated the weekly exercise sheets, the physics lab course, and math courses as stressors; later on, preparation for exams and the exams themselves emerged as the most important stressors. Together with the students’ self-estimated workloads that correlate with the PSQ scores, we can create a coherent picture of stress perceptions among first-year physics students, which builds the basis for supportive measures and interventions. Published by the American Physical Society 2024

MODELLING OF SOCIO-PSYCHOLOGICAL ADAPTATION OF AN INDIVIDUAL TO DIGITAL RISKS IN EDUCATION AND PROFESSIONAL SELF-DETERMINATION

Automated semantic analysis and topic modelling methods were first applied to a large corpus of public online communities and discussions to analyse strategies for responding to digital risks in modern society. A large array of public data on profiles of the social network “Vkontakte” and their subscriptions to online communities was used to train a predictive model of individual adaptation to risks in the field of education and professional self-determination. Based on the results of thematic modelling, three topics of subscriptions to online communities were identified as signs of psychological adaptation: preparation for exams, self-development and “popular” psychology, education and science. The developed version of the predictive model of psychological adaptation showed high accuracy and the importance of such factors as age, gender and place of residence for individual adaptation to digital risks in the field of education and professional self-determination.

Development of linear bearing equipment for modal testing of low-frequency weakly damped spacecraft structures

This article presents the results of a study of the bearing capacity and dissipative properties of an aerostatic linear bearing developed at JSC RESHETNEV for modal testing of complex structures. When selecting equipment for modal testing, the main condition is the requirement to minimize the distortions introduced into the determined dynamic characteristics: frequencies of natural vibration modes, the vibration modes themselves, as well as modal masses and damping coefficients. In other words, all equipment used for ground-based modal testing should ideally have zero added mass, stiffness and friction. The main systems containing elements that create dissipative forces that affect the determination of damping coefficients are systems for weight compensation and vibration excitation on natural modes. The weight compensation system usually contains either elastic elements or a system of guides with rolling or sliding bearings. If the former bring additional rigidity and mass to the test object, the latter bring mass and friction (dry or viscous), which increases the error in determining the dynamic characteristics. The excitation of vibrations on natural modes, in most cases, is carried out by electrodynamic vibrators consisting of a magnetization coil (or permanent magnet) and a movable coil moving in a magnetic gap. The movable coil is oriented in the magnetic gap using a special system containing either elastic elements or a linear guide bearing. Vibrators with elastic coil suspension elements cannot be used for modal tests of extended structures with low rigidity. The problem of creating an ideal bearing to replace classic linear (sliding or roller) ones arose during preparation for modal tests of the wing of a solar battery of a spacecraft (SC). Aerostatic bearings (supports) have virtually zero friction and sufficient load-bearing capacity, in which compressed air acts as a lubricant, eliminating physical contacts of the interacting surfaces. To confirm the possibility of using aerostatic bearings in equipment for conducting modal tests of extended structures with low frequencies of natural oscillations, comparative tests of a roller and aerostatic bearing were carried out. During the tests, optimal air flow parameters (nozzle diameter, operating pressure and gap) were selected, which ensure the required load-bearing capacity for radial forces and torques (bending and torsion). A comparative assessment of dissipative properties was carried out when measuring the attenuation parameters of single-mass harmonic oscillators, which include aerostatic and roller linear bearings. With a nozzle diameter of 0.6 mm, a working gap of 40 μm and a bearing input pressure of 1.0 bar, the logarithmic decrement of oscillations of the harmonic oscillator with an aerostatic bearing was 0.084, which is more than 28 times lower than the logarithmic decrement of oscillations of an oscillator with a roller bearing. The conducted studies confirmed the possibility of using the developed aerostatic bearing in test systems used in modal tests of large-sized transformable spacecraft structures.

7870 Exploring The Role Of ChatGPT In Pediatric Endocrinology Education; Exam Preparation And Question Generation

Abstract Disclosure: J. Tarkoff: None. A.G. Martinez Sanchez: None. Large language models (LLMs) hold substantial promise for improving physician knowledge and expertise. Their role in medical education and the generation of diverse diagnoses can be crucial, potentially leading to positive effects on clinical outcomes. The New England Journal of Medicine pediatric case challenges have examined ChatGPT [1]. Yet, its performance in specialized areas like Pediatric Endocrinology remains unexplored. This study assesses the effectiveness of ChatGPT 4 in responding to questions from the Pediatric Endocrine Self-Assessment Program (PESAP). It also examines if the AI is suitable for creating an educational quiz for residents and fellows. Methods: ChatGPT 4 underwent testing with questions from the 2021-2022 version of PESAP, utilizing the prompt: “Can you assist from the perspective of a pediatric endocrinologist with the following patient case”. Responses were evaluated for initial correctness, and performance was analyzed across various competency categories corresponding to the 7 “umbrella sections” of the tool (Adrenal, Bone, Carbohydrate and Lipid Metabolism/Obesity, Growth, Pituitary, Reproductive System, and Thyroid). Subsequently, we personalized the model by incorporating the questions and detailed responses from the PESAP. This customization resulted in a model that was then utilized to create a 10-question proof-of-concept quiz for four board-certified pediatric endocrinologists. The quiz included a scoring system designed to measure the extent and depth of ChatGPT knowledge. Results: ChatGPT 4 accurately answered 52% of PESAP questions, demonstrating varying performance across specific categories, ranging from 30% (Adrenal) to 78% (Reproductive System). In 16 questions, ChatGPT 4 did not provide an initial answer, requiring a specific request for a response. For questions related to thyroid cancer, explicit prompts were necessary to instruct responses based on the American Thyroid Association 2015 guidelines. In the endocrinologist quiz, the average score was 80%, ranging from 60% to 100%. Discussion: Currently, using ChatGPT 4 as the final diagnostic tool, especially in pediatric endocrinology, should be approached with caution, based on our assessment. However, when incorporating distinct Pediatric Endocrinology case studies, ChatGPT 4 successfully generated valuable educational questions, reinforcing fundamental concepts in the field. We anticipate that as LLMs advance and receive direct medical training, the out-of-the-box diagnostic accuracy will improve, leading to a transformative impact on medical education through this technology.

Measurement of anisotropic airflow resistance characteristics of mineral wool samples

In the field of acoustics, the airflow resistance of a porous materials like stone wool is one of the governing parameters. As a starting point, measuring the airflow resistance in the normal direction can be used for good estimations of sound-absorbing abilities when using empirical models. However, more complex models, like equivalent fluid models and Biot models, need more input parameters. The next natural step is to move into 2D and 3D interactions. An obstacle to overcome is obtaining accurate input parameters to qualify the models. The production process of stone wool introduces an inherent geometric anisotropy in the material. The aim of the study is hence to develop test and sample preparation methods that enable the measurement of the airflow resistance of stone wool sample in 3 directions by means of testing a cubic specimen. The airflow resistance was measured using a modified unidirectional static airflow apparatus. The paper presents test results obtained with the apparatus for a range of stone wool samples of varying densities. The results show noticeable differences in airflow resistance of more than 1.5 times between testing directions. This paper also, includes comparisons to results obtained using an alternating airflow method as per ISO 9053-2:2020.

학교현장실습학기제에 대한 사범대학 학생들의 인식

This study analyzes the results of a demand survey conducted among students of the College of Education prior to their participation in a pilot program for the semester-long teaching practicum. Among all the students surveyed, 49.3% expressed their willingness to participate in the practicum, while 50.7% were unwilling to participate. The most common reason for wanting to participate was to confirm their aptitude for teaching, cited by 35.6% of respondents. This was followed by a desire to better understand schools and students, at 30.8%. In contrast, reasons such as preparing for the teacher certification exam and enhancing teaching expertise were less frequently mentioned. The main reasons for not participating were a lack of preparation for the teacher certification exam(29.9%), the burden of major coursework(27.1%), and the belief that the existing four-week practicum was sufficient(27.1%). Based on the results of study, we propose some recommendations for the operation of the semester-long teaching practicum. First, it is necessary to discuss whether it is appropriate to implement the practicum for all students. Second, there was a significant gap between the number of students who expressed a willingness to participate and those who actually participated, indicating a need for incentives to encourage participation. Third, more systematic guidance is required for the education provided before and after the practicum, as well as for mentoring and coaching during the practicum. Finally, while extending the practicum period is important, it is even more crucial to establish a comprehensive educational plan.

Exploration of medical students’ approach to progress test preparation

Introduction: Medical students are expected to develop competencies in applying clinical knowledge. Progress testing is an assessment for learning and is intended to assist in knowledge acquisition and to promote ongoing recall. This study explored student preparation for progress tests (PTs), relationships between approach and performance, and patterns that could assist with targeting learning support. Methods: A cross-sectional survey exploring study approach and learning context, comprising multi-choice and open-ended responses, was administered to students during their clinical years (n = 297). Quantitative data was analysed using descriptive statistics and comparative analysis, and qualitative data was categorised. Results: One hundred twenty-nine students responded (43.4%), with most demonstrating a stable PT performance over time. Twenty-two students had dynamic changes in their aggregate grades. Poor early PT performance was associated with developing an improvement strategy (χ2 6.954, p = 0.008). Students never falling below satisfactory were less likely to have a strategy (χ2 10.084, p = 0.001). All poorly performing students were using practice question banks, but this was not true for students who scored satisfactorily. The need for pastoral care was associated with poorer performance (χ2 4.701, p = 0.030). Conclusions: Student approaches to PT preparation are diverse, however there are correlations between preparation factors and performance outcomes. Students with poor early performance demonstrated improved results over time that may be attributed to targeted support and preparation strategies. Widespread use of practice questions may not be sufficient to impact results without additional strategies. External impacts to performance were common, and barriers to accessing pastoral care were evident. The feedback dashboard was underutilised, suggesting a need to improve feedback literacy and ensure this is fit for purpose.

The Changing Educational Landscape for Sustainable Online Experiences: Implications of ChatGPT in Arab Students’ Learning Experience

The integration of artificial intelligence (AI) into education is rapidly transforming traditional paradigms of teaching and learning. ChatGPT, an advanced AI system capable of sophisticated language generation, represents a potentially disruptive innovation in this sphere. This study employed a descriptive cross-sectional design using a cross-sectional approach to examine ChatGPT’s emerging role in reshaping students’ learning experiences within higher education. A survey of 473 undergraduate students at King Faisal University, Saudi Arabia assessed ChatGPT’s usage patterns, effectiveness, and implications across diverse learning domains. Data were collected through a structured online survey distributed over a month and analyzed using quantitative measures (i.e., SPSS). Sixty precent (60%) of the students reported using ChatGPT for homework assistance, with 27.7% doing so weekly. Additionally, 45.5% utilized it for research, 35.5% for exam preparation, and approximately 30% for language learning and content discussions. Over 60% of the students recognized moderate to significant positive impacts of ChatGPT on their academic performance, research skills, and technical competencies. However, 38.7% reported no discernible effects on critical thinking. Factor analysis identified engagement as a key pathway for ChatGPT to enrich learning, with usage strongly linked to participation and motivation. Regression analysis determined usage frequency, satisfaction, and perceived usefulness as significant predictors of ChatGPT’s academic effectiveness, evidenced by beta coefficients of 0.21 for usage frequency and 0.25 for satisfaction. The findings showcase ChatGPT’s promising versatility as an AI-powered educational tool, while emphasizing the need for ethical frameworks, balanced expectations, and holistic adoption strategies to maximize benefits and minimize risks. Further research into pedagogical integration capabilities and evolving impacts will be critical as advanced AI becomes increasingly pervasive throughout education.