College Entrance Examination Research Articles

E-Assessment Architecture for Higher Education: A Case Study of University Entrance Exam, Higher Education of Afghanistan

Purpose: The main aim of this study is to demonstrate that which e-assessment architecture can be useful and effective for the higher education sector in Afghanistan. Methodology: The research method was design science, where 100 questionnaires were distributed for specifying the functional and non-functional requirements of the e-assessment system. Questionnaires were distributed to 50 lecturers, 20 Administrators and 30 graduate students. This study conducted the structured interviews for analyzing the e-assessment architectures and find an applicable and accurate e-assessment architecture for university entrance exam. In this study, interviewed with five participants and the interview has 24 questions. This study used close-ended questions in the interview and considered different perspectives including interoperability, security, reusability, performance, scalability and flexibility for analyzing the e-assessment architectures. Findings: After analyze the interview results, this study propose the architecture based on NREN for the university entrance exam of Afghanistan’s higher education. This study used the Architecture Tradeoff Analysis Method (ATAM) for the evaluating the e-assessment system architecture based on NREN. For this purpose, ATAM workshop established and evaluated the proposed architecture by fifteen experts. Unique Contribution to Theory, Practice and Policy: This study recommended the e-assessment application architecture. After the literature review, we carried out the survey in different higher education institutes, including Kabul Polytechnic University, Kabul University and Kabul Education University and the respondents were the lecturers, students, administrators and the higher education ministry decision makers. The study evaluates the requirements for the e-assessment system.

Mass Spectrometry in Exam Questions (8): The Common Test for University Admissions (2024) provided by the National Center for University Entrance Examinations, Japan, the First Half

Mass Spectrometry in Exam Questions (8): The Common Test for University Admissions (2024) provided by the National Center for University Entrance Examinations, Japan, the First Half

Study on the Relationship Between Parental Autonomy Support, Academic Self-Efficacy, and Career Adaptability of High School Students

This study investigates the relationship between parental autonomy support, academic self-efficacy, and career adaptability of high school students in the context of the new college entrance examination system. Using the Career Adaptability Scale, the Parental Autonomy Support Questionnaire, and the Academic Self-Efficacy Scale, this research tested 440 first-year high school students from four schools in Sichuan Province. The results reveal that (1) parental autonomy support significantly positively predicts career adaptability, indicating that more autonomy support from parents correlates with higher levels of career adaptability in students; (2) parental autonomy support not only directly predicts career adaptability but also affects it through the mediation of academic self-efficacy in students, which plays a partial mediating role.

Exam scheduling under pandemic conditions: A mathematical model and decision support system

The scheduling of university exams is a complex task that involves various constraints such as administrative limits, pedagogical needs, student volume, and different courses. The emergence of Covid-19 and future pandemics has added new constraints related to infection prevention and contact tracing. To address these challenges, this study proposes a multi-objective mathematical model that considers university resources, reduced classroom occupancy, and minimized student interaction. The model aims to minimize violations of pandemic-related constraints and categorize exams by difficulty. To facilitate scheduling for entire faculties or universities, a Genetic Algorithm based web-based decision support system is developed. With these tools, the study successfully created an optimal schedule for eight departments simultaneously.

The long‐run educational benefits of high‐achieving classrooms

AbstractThis paper examines how placement in high‐achieving classrooms within high school impacts students’ short‐ and longer‐term academic outcomes. Our setting is a large and selective Chinese high school, where first‐year students are separated into high‐achieving and regular classrooms based on their performance on a standardized exam. Classrooms differ in terms of peer ability, teacher quality, and class size, as well as level and pace of instruction. Using newly collected administrative data and a regression discontinuity design, we show that high‐achieving classrooms improve math test scores by 23% of a standard deviation, with effects persisting throughout the 3 years of high school. Impacts on performance in Chinese and English language subjects are more muted. Importantly, we find that high‐achieving classrooms raise enrollment in elite universities by 17 percentage points, as they substantially increase scores on the national college entrance exam—the sole determinant of university admission in China. We provide suggestive evidence that the most likely mechanism driving our results is exposure to higher‐quality teachers.

Teaching Strategies for the New Continuation Writing Task in China's College Entrance Examination Guided by Scaffolding Theory: A Case Study of the

Teaching Strategies for the New Continuation Writing Task in China's College Entrance Examination Guided by Scaffolding Theory: A Case Study of the

Exploring Sleep Duration and Insomnia Among Prospective University Students: A Study with Geographical Data and Machine Learning Techniques.

Sleep disruptions among prospective university students are increasingly recognized for their potential ramifications on academic achievement and psychological well-being. But, information regarding sleep issues among students preparing for university entrance exams is unknown. Thus, this study aimed to investigate the prevalence and factors associated with sleep duration and insomnia among university entrance test-takers in Bangladesh, utilizing both traditional statistical analyses and advanced geographic information system and machine learning techniques for enhanced predictive capability. A cross-sectional study was conducted in June 2023 among 1496 entrance test-takers at Jahangirnagar University, Dhaka. Structured questionnaires collected data on demographics, academic information, and mental health assessments. Statistical analyses, including chi-square tests and logistic regression, were performed using SPSS, while machine learning models were applied using Python and Google Colab. Approximately 62.9% of participants reported abnormal sleep duration (<7 hours/night or >9 hours/night), with 25.5% experiencing insomnia. Females and those dissatisfied with mock tests were more likely to report abnormal sleep duration, while repeat test-takers, those with unsatisfactory mock test results, or anxiety symptoms had a higher risk of insomnia. Machine learning identified satisfaction with previous mock tests as the most significant predictor of sleep disturbances, while higher secondary school certificate GPA had the least influence. The CatBoost model achieved maximum accuracy rates of 61.27% and 73.46%, respectively, for predicting sleep duration and insomnia, with low log loss values indicating robust predictive performance. Geographic analysis revealed regional variations in sleep disturbances, with higher insomnia prevalence in some southern districts and abnormal sleep duration in northern and eastern districts. Sleep disturbances are prevalent among prospective university students and are associated with various factors including gender, test-taking status, mock test satisfaction, and anxiety. Targeted interventions, including sleep education and psychological support, hold promise in ameliorating sleep health and overall well-being among students, potentially enhancing entrance test performance.

English Writing Anxiety in Chinese High School Students: Causes and Consequences

Second language (L2) writing anxiety has been widely discussed by researchers, for writing anxiety has its specific causes and may affect peoples L2 writing performance. In the Chinese context, high school students undergo exam-orientated education and face the college entrance exams. They may have special causes and may suffer from specific consequences of English writing anxiety. The research is done in a normal high school in Zhejiang Province, focusing on the causes and consequences of English writing anxiety in Chinese high school students. The research used a questionnaire to collect data and analyze them in SPSS. Through exploratory factor analysis (efa), the research finds out that exams, fear of errors, and writing difficulties may be the main causes of Chinese high school students writing anxiety. The research also collected students recent exam grades and conducted co-relation analysis and regression analysis, which shows that English writing anxiety exerts negative impact on Chinese students English writing performance.

Research on the Application of 5E Teaching Model in Senior English Writing Teaching

Writing, as a pivotal part of English language teaching, provides an important platform for cultivating students’ core competencies and reflects students’ comprehensive language application ability and language expression ability as well. With the reform of the new college entrance examination, the difficulty of the writing section has increased. Thus, how to adapt to the reform of the college entrance examination and explore new writing teaching methods has become a widely concerned issue among front-line high school teachers. Based on the analysis of the connotation and elements of the 5E teaching model, as well as the current situation of writing teaching, this study combines the 5E teaching model with writing teaching, aiming to explore new effective teaching models, promote reform of writing teaching, and improve the quality of writing teaching.

Application of Schema Theory in English Reading Comprehension Teaching in Senior High School

English reading is a basic language skill, and the level of English reading comprehension is directly related to the level of learners’ language ability. In recent years, the new curriculum standards and the new college entrance examination reform have put forward higher requirements for high school students’ English reading comprehension ability. However, English teachers pay much more attention to vocabulary, sentence patterns and grammar knowledge, and to some extent neglect the cultivation of the cultural knowledge, genre structure and reading strategies at present. English reading teaching based on schema theory emphasizes linguistic knowledge as the basis, activating the existing schema, enriching the background knowledge and grasping the discourse structure, so as to achieve a comprehensive understanding of the text. Therefore, this paper combines schema theory with English reading teaching, and analyzes how to effectively use schema theory to help students effectively read and improve their reading ability from three stages: before reading, while reading and after reading.

Evaluating the fairness of a high-stakes college entrance exam in Kuwait

The use of college entrance exams for facilitating admission decisions become controversial, and the central argument is around the fairness of test scores. The Kuwait University English Aptitude Test (KUEAT) is a high-stakes test, but very few studies have examined the psychometric quality of the scores for this national-level assessment. This study illustrates how measurement approaches can be used to examine the fairness issues in educational testing. Through a modern view of fairness, we assess the internal and external bias of KUEAT scores using differential item functioning analysis and differential prediction analysis, respectively, and provide a comprehensive fairness argument for KUEAT scores. The analysis for examining the internal evidence of bias was based on 1790 examinees’ KUEAT scores in November 2018. KUEAT scores and first-year college GPAs of 4033 students enrolled in KU were used for assessing the external evidence of bias. Results revealed many items showing differential item functioning across student subpopulation groups (i.e., nationality, gender, high school majors, and high school types). Meanwhile, KUEAT scores also predicted college performance differentially by different student subgroups (i.e., nationality, high school majors, and high school types). Discussion and implications on the fairness issues of college entrance tests in Kuwait are provided.

The China's College Entrance Examination Research: A Literature Review from 2014 to 2023

The China's College Entrance Examination Research: A Literature Review from 2014 to 2023

Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via Self-Supervised Learning: Prospective, Exploratory, Observational Study.

Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of the worldwide disease burden. However, collecting and annotating wearable data is resource intensive. Studies of this kind can thus typically afford to recruit only a few dozen patients. This constitutes one of the major obstacles to applying modern supervised machine learning techniques to MD detection. In this paper, we overcame this data bottleneck and advanced the detection of acute MD episodes from wearables' data on the back of recent advances in self-supervised learning (SSL). This approach leverages unlabeled data to learn representations during pretraining, subsequently exploited for a supervised task. We collected open access data sets recording with the Empatica E4 wristband spanning different, unrelated to MD monitoring, personal sensing tasks-from emotion recognition in Super Mario players to stress detection in undergraduates-and devised a preprocessing pipeline performing on-/off-body detection, sleep/wake detection, segmentation, and (optionally) feature extraction. With 161 E4-recorded subjects, we introduced E4SelfLearning, the largest-to-date open access collection, and its preprocessing pipeline. We developed a novel E4-tailored transformer (E4mer) architecture, serving as the blueprint for both SSL and fully supervised learning; we assessed whether and under which conditions self-supervised pretraining led to an improvement over fully supervised baselines (ie, the fully supervised E4mer and pre-deep learning algorithms) in detecting acute MD episodes from recording segments taken in 64 (n=32, 50%, acute, n=32, 50%, stable) patients. SSL significantly outperformed fully supervised pipelines using either our novel E4mer or extreme gradient boosting (XGBoost): n=3353 (81.23%) against n=3110 (75.35%; E4mer) and n=2973 (72.02%; XGBoost) correctly classified recording segments from a total of 4128 segments. SSL performance was strongly associated with the specific surrogate task used for pretraining, as well as with unlabeled data availability. We showed that SSL, a paradigm where a model is pretrained on unlabeled data with no need for human annotations before deployment on the supervised target task of interest, helps overcome the annotation bottleneck; the choice of the pretraining surrogate task and the size of unlabeled data for pretraining are key determinants of SSL success. We introduced E4mer, which can be used for SSL, and shared the E4SelfLearning collection, along with its preprocessing pipeline, which can foster and expedite future research into SSL for personal sensing.

Research on Optimization of High School Mathematics Teaching Strategies from the Perspective of Core Literacy Cultivation

Currently, cultivating students’ core subject literacy has become an important direction of high school education reform and the main teaching goal of various subjects in high school. As a subject of the college entrance examination and a highly practical high school subject, high school mathematics teachers should also keep up with the advancement to optimize classroom teaching activities, adjust teaching strategies, and cultivate students to form good core mathematical literacy. This article will explore the importance of high school mathematics teaching from the perspective of core literacy, and propose optimization teaching strategies, in order to provide corresponding references for high school mathematics teaching reformation.

The Dilemma of Difficulty in Breaking through English Listening in the College Entrance Examination and its Coping Strategies

The Dilemma of Difficulty in Breaking through English Listening in the College Entrance Examination and its Coping Strategies

Overview of the Foreign Language Sections in the Matriculation Exam in Poland and the University Entrance Exam in Türkiye

This paper highlights the contrasting approaches to foreign language assessment in high-stakes examinations for university education in Poland and Türkiye, focusing on content, task types, and language skills. In Poland, language acquisition is seen as a tool for effective communication, while in Türkiye, it is often perceived as rote memorization of grammar and vocabulary. This difference in mindset is influenced by prevailing assessment practices, where Türkiye’s evaluation methods prioritize memorization, leading to a diminished emphasis on communication and practical language use. This disparity is reflected in the EF English Proficiency Index, with Poland ranking high and Türkiye ranking low in language proficiency. Neglected language skills, such as speaking and listening, further exacerbate the issue. Despite discussions on transforming assessment practices for decades, Türkiye has made little progress. The practicality of multiple-choice-based tests in Türkiye is noted, but their limitations in testing language skills comprehensively are acknowledged.

An Autoethnography about a Career Educator’ Experience of her Child’s College Entrance Exam Preparation Process

An Autoethnography about a Career Educator’ Experience of her Child’s College Entrance Exam Preparation Process

Factors Associated with Suicidal Ideation in Last-course High School Students Facing the University Entrance Test in Spain

Suicidal ideation has been associated in different studies with emotional disturbances, including anxiety, depressive symptoms and burnout. At the moment, there are not many studies that have explored this association in students who face the university entrance examination in Spain. In this research, our main objective was to explore the association between positive suicidal ideation and anxiety, depressive symptoms and burnout in students who were taking these tests. The study involved 402 last-course high school students who were taking the assessment tests in Granada (Spain), aged between 17 and 24. All of them answered to a survey containing sociodemographic variables, the Spielberger State-Trait Anxiety Inventory (STAI), the Zung’s Self-Rating Depression Scale, the one-dimensional scale of Student Burnout and the Positive and Negative Suicidal Ideation Inventory. The results obtained indicate a clear and sig-nificant correlation between positive suicidal ideation, anxiety, depressive symptoms and burnout. Of these three variables, the one that best predicts the presence of suicidal ideation is depressive symptoms. Knowing the presence of emotional disturbances and dysfunctional states in these students is important in preventing and intervening in this ideation in students.

Teach Writing by Process Writing Approach

The college entrance examination (gaokao) has placed higher demands on students' writing skills, and traditional writing instruction methods no longer meet the needs of talent cultivation today. The process writing approach is one of the most popular methods for teaching writing. This article, based on a comparison of the product writing approach and the process writing approach, focuses on the characteristics and specific implementation stages of the process approach. Finally, two suggestions are proposed in the hope of assisting frontline teachers in improving English writing instruction in junior and senior high schools.

ALIGNMENT BETWEEN CURRICULUM STANDARDS AND ASSESSMENT IN UNDERSTANDING CHEMICAL REACTION PRINCIPLES AT UPPER-SECONDARY SCHOOLS

This study utilized the SEC (Survey of Enacted Curriculum) method to examine the alignment between Chinese high school chemistry curriculum standards (HSCCS) and the assessment of ‘Chemical Reaction Principles’ in the National College Entrance Examinations (NCEEs). The HSCCS and NCEEs were coded into two-dimensional matrices separately using SPSS, MATLAB, and EXCEL. The alignment coefficients were analyzed both macroscopically and specifically based on two dimensions: themes and cognitive levels. The findings indicated a generally low alignment between NCEEs and HSCCS in the ‘Chemical Reaction Principles’ domain, and no statistically significant alignment was observed. Comparing Porter alignment coefficients revealed a gradual increase in the overall alignment level between 2018–2022 NCEEs and HSCCS due to curricular reforms. Further specific analyses and comparisons highlighted significant discrepancies between NCEEs and HSCCS concerning themes and cognitive levels. Regarding themes, ‘Ionic Reactions and Equilibrium in Aqueous Solutions’ showed substantial alignment between NCEEs and HSCCS. However, for ‘Application of Ionic Reactions and Equilibrium’ and ‘Systems and Energy,’ NCEEs diverged significantly from or exceeded HSCCS requirements. Concerning cognitive levels, NCEEs demanded higher levels of student cognition compared to HSCCS. Keywords: alignment, chemical reaction principles, content analysis, curriculum standards, upper-secondary schools