Academic Test Research Articles

The Effect of Historical Places Through Virtual Museums on Students' Academic Achievement And Attitudes Towards The Course In Social Sciences Course Concept Teaching

This research, 7. the classroom social studies course was conducted in order to determine the effect of historical sites on students' academic achievements and attitudes towards the course through virtual museums in concept teaching. In line with the aim, 20 concepts included in the social studies curriculum were selected. A 20-question academic achievement test was prepared and applied to be applied to students in relation to these concepts. In addition, a 35-item attitude scale was applied to determine the students' attitudes towards the Social studies course. The study group of the research consists of 40 7th grade students (20 experimental, 20 control). The study was carried out over a total period of 3 weeks. The experimental group was taught concepts through virtual museums in historical places, and the control group was taught according to the Social Studies curriculum. SPSS, which is a statistical analysis program, was used for the analysis of quantitative data. In the measurements related to the research, dependent and independent variable t test, mean, standard deviation values were calculated. According to the results of the analysis, it has been determined that the use of virtual museums with historical sites in social studies course concept teaching enables more effective learning compared to traditional methods and creates significant differences in students' attitudes towards social studies course.

A Low Mach Preconditioned Harmonic Balance Solver for Cavity Flutter Computations

Abstract Labyrinth seal flutter is a critical phenomenon in turbomachinery, as it can lead to severe structural vibrations and potential component damage. Accurate prediction and mitigation of flutter are paramount to ensuring the reliability and performance of modern turbomachinery systems. This paper explores the numerical computation of a labyrinth seal flutter test case using a low Mach preconditioned harmonic balance (HB) solver and investigates how this approach can improve the accuracy and response time of flutter computations. HB solvers have gained prominence in turbomachinery computations for their ability to efficiently capture unsteady flow phenomena and significantly reduce computational time compared to time-domain analyses. In labyrinth seals, however, the flow is often characterized by low Mach numbers, and preconditioning for these conditions has been shown to significantly improve convergence and accuracy. The goal of this paper is to demonstrate how to implement low Mach preconditioning in a HB solver in the frequency domain. We employ iterative preconditioning to alleviate the stiffness associated with density-based solvers under low Mach conditions and analyze the effect of the preconditioning parameters on the convergence rate. Furthermore, we address inaccuracies linked to the classical Roe solver in low Mach scenarios by adapting it to the low Mach preconditioned governing equations. Through the combined utilization of iterative preconditioning and a preconditioned Roe solver, this study aims to improve convergence rates and the overall quality of flutter predictions. We demonstrate the method with an academic labyrinth seal test case originally presented by Corral et al. (“Higher Order Conceptual Model for Labyrinth Seal Flutter,” ASME J. Turbomach., 143(7), p. 071006). While previous investigations have primarily relied on linearized frequency domain solvers and reduce-order models, in this research a preconditioned HB solver is applied to this test case.

Using Keystroke Behavior Patterns to Detect Nonauthentic Texts in Writing Assessments: Evaluating the Fairness of Predictive Models

AbstractThe emergence of sophisticated AI tools such as ChatGPT, coupled with the transition to remote delivery of educational assessments in the COVID‐19 era, has led to increasing concerns about academic integrity and test security. Using AI tools, test takers can produce high‐quality texts effortlessly and use them to game assessments. It is thus critical to detect these nonauthentic texts to ensure test integrity. In this study, we leveraged keystroke logs—recordings of every keypress—to build machine learning (ML) detectors of nonauthentic texts in a large‐scale writing assessment. We focused on investigating the fairness of the detectors across demographic subgroups to ensure that nongenuine writing can be predicted equally well across subgroups. Results indicated that keystroke dynamics were effective in identifying nonauthentic texts. While the ML models were slightly more likely to misclassify the original responses submitted by male test takers as consisting of nonauthentic texts than those submitted by females, the effect sizes were negligible. Furthermore, balancing demographic distributions and class labels did not consistently mitigate detector bias across predictive models. Findings of this study not only provide implications for using behavioral data to address test security issues, but also highlight the importance of evaluating the fairness of predictive models in educational contexts.

3D limit analysis of reinforced concrete with sliding along smeared cracks

Limit analysis (LA) is successfully used for investigating the bearing capacity of reinforced concrete (RC) structures. Some cautions must be taken when using this method for RC since the concrete component exhibits a softening behavior with decreasing strength and limited ductility. A commonly adopted provision consists of considering isotropic reduced values of concrete strength to be input in the analysis (empirical effectiveness factors). In this paper, an alternative and completely new approach is proposed and investigated in which concrete strength is weakened in a more targeted manner. To that purpose, the commonly used 3D truncated Mohr-Coulomb (TMC) criterion is adopted to classically describe the compressive, tensile, and shear failure of concrete. However, TMC is here in an original way enriched by additional constraints that allow to account for weakness and anisotropy induced by preferential failure patterns, assumed a priori. The limit analysis approach is then formulated for two dual analyses in the convex optimization framework, making it possible to quantify the numerical error and obtain a lower and an upper bound of the limit load. Numerical examples illustrate the agreement of the formulation with academic results and laboratory tests.

Meningkatkan Prestasi Akademik dan Keterampilan Kerja Sama Peserta Didik Menggunakan Model Problem-Based Learning (PBL) pada Materi Manusia Berkembang Berkat Peran Sesama di Kelas VII SMP Negeri 4 Kayan Hilir

This study aims to improve the academic achievement and teamwork skills of 7th-grade students at SMP Negeri 4 Kayan Hilir by using the Problem-Based Learning (PBL) model on the topic of "Human Development Through the Role of Others." The research was conducted in two cycles, each consisting of planning, implementation, observation, and reflection. The subjects of the study were 20 7th-grade students. Data collection instruments included academic achievement tests and teamwork skills observation sheets. The results of the study showed an increase in academic achievement, from an average score of 64 in the pre-cycle to 81 in cycle II. Additionally, the students' teamwork skills improved from the "sufficient" category to "good" in cycle II. Thus, the PBL model was effective in improving both the academic achievement and teamwork skills of the students.

Estimating Students' Academic Success in the Preclinical Stage of Undergraduate Medical Education Using the Admission Test Approach.

Medical schools face substantial challenges in objectively selecting the best applicants, and the admission process can impact medical students' academic performance. This study aimed to estimate the students' academic success in the preclinical stage of undergraduate medical education using admission tests. This cross-sectional study was conducted on 1,193 students' records from the 2014 to 2019 cohorts. The students' admission data comprised the cohort, sex, admission track, psychological test, and academic tests. The academic success was based on the student's end-year academic evaluation. Data were analyzed using contingency and Kendall's tau b tests with IBM® SPSS® Statistics version 16.0 for Windows. Most of the 1,193 preclinical medical students' records included in the study were females (68.1%), from the regular admission track (78.5%), from the considered psychology test category (52.8%), and had an academic admission test of less than or equal to the median. (51.6%). Most students (89.7%) met all the academic requirements to pass the end-year evaluation. The bivariate analyses showed significant correlations between academic success and cohort (p<0.001), psychology test (p=0.005), and academic test (p<0.001). The analyses showed no significant correlation between academic success and sex (p=0.324), and admission track (p=0.128). This study indicated that cohort and psychology tests could estimate the student's academic success at the preclinical stage of undergraduate medical education. The admission criteria related to the academic tests during the admission process should be re-evaluated, so that the academic tests could select the best students among the applicants.

Impact of Artificial Intelligence Chatbots on Student Well-being and Mental Health: A Systematic Review

Students in schools and colleges face some challenges, including rigorous academic schedules, academic work load, standardized tests, and assignments deadline, which can contribute to significant stress and mental health risks. Thus, numerous studies have been conducted to control stress between students, such as self-guided stress management programs. This paper reviews several studies published between 2019 and 2023 exploring the impacts of deploying state-of-the-art artificial intelligence chatbots which are used to boost and manage psychological disorders and mental health symptoms such as anxiety, depression, fear, and worry between prospective and current undergraduate students. This study outlines the key phases of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). It begins with screening (115) articles and subsequently includes (13) articles for intensive review, which all focus on psychological disorders and mental health conditions that can be influenced by the conversational agents and chatbots. However, the results revealed that anxiety and depression are the main psychological disorders that can be influenced by conversational agents and chatbots. Moreover, this review revealed multiple cases of universities and schools, emphasizing the implementation of chatbots for both learning and advising functions. The Systematic Literature Review (SLR) in this study is constrained to the specific databases, and the search keywords were limited to the article title fields only; which excluded the abstracts. This could have caused some missing relevant studies. In future work, other essential databases will be included, such as Scopus and WoS. In addition, we will include more information about the technique and the complexities of using the chatbot as it may have a significant impact on student behaviors and emotions.

Cognitive, Social, and Emotional-Behavioral Outcomes in Children and Adolescents With Beckwith-Wiedemann Syndrome.

Although Beckwith-Wiedemann syndrome spectrum (BWSp) is not usually associated with intellectual disability, recent evidences calls for further investigation of cognitive development and academic skills in children with BWSp. Moreover, research has documented social difficulties and emotional-behavioral problems associated with BWSp. Nevertheless, a full characterization of socio-emotional development in BWSp is still lacking. In the current study, cognitive and socio-emotional development was assessed in 29 children with BWSp aged 5-18 years, using a test of nonverbal intelligence, a neuropsychological battery covering multiple domains, academic skills tests, and questionnaires evaluating autistic traits and emotional-behavioral problems. As expected, most participants showed adequate performance in cognitive tests. However, the findings also highlighted greater difficulties in language than visuospatial processing, strengths in social perception, as well as slowness in reading and mental calculation. The assessment of emotional-behavioral difficulties indicated a prevalent phenotype characterized by increased anxiety, low self-esteem, social withdrawal and a tendency to control externalizing reactions, but no associations with autistic traits, cognitive outcomes, and the clinical score proposed by the recent Consensus statement. Increased social perception and internalization problems likely result from coping strategies with social and care-related stress. Overall, the findings of this study inform clinical management and genetic counseling for children and adolescents with BWSp.

The Effect of Cooperative Learning on Academic Performances and Computational Thinking Skills in the Computational Problem-Solving Approach

In this study, we aimed to investigate the impact of cooperative learning on the computational thinking skills and academic performances of middle school students in the computational problem-solving approach. We used the pretest-posttest control group design of the quasi-experimental method. In the research, computational problem-solving activities regarding 6th graders' goals of the "heat and matter" unit, were applied individually by Group 1 and cooperative learning by Group 2. These activities required students to use computational thinking skills and code using the Python programming language. The study involved 34 students from the 6th grade of a private middle school located in the capital city of Turkey. The Computational Thinking Test (CTt) and an academic achievement test were used as pre-tests and post-tests to monitor students' computational thinking skills and academic performances. Additionally, computational problem-solving activities were scored to track the progress of students' computational thinking abilities. Non-parametric Mann Whitney U and Wilcoxon T-tests were utilized to analyze the progression of pupils' computational thinking abilities and academic success, and ANCOVA was used to analyze CTt scores. Qualitative data were collected through semi-structured interviews at the end of the process to determine students' views on the computational problem-solving process. Results revealed a significant increase in students' academic achievement and computational thinking skills in both groups. A comparison of post-test scores showed no significant difference between groups. It is anticipated that the research results will make meaningful contributions to the literature concerning the progress of computational thinking skills in secondary school students.

Improving the blade tip clearance measurement method based on blade tip timing: Accounting for rotor speed variations and non-uniform blade-by-blade tip clearance

The Blade Tip Clearance (BTC) measurement method based on Blade Tip Timing (BTT) suffers from poor accuracy under changing speed conditions and in the determination of blade-by-blade tip clearance. To address these challenges, this paper presents the Time of Arrival Polynomial Fitting (ToA-PF) method for achieving high-precision tip clearance measurements under variable speed conditions. Additionally, a correction method is introduced to effectively mitigate measurement errors in blade-by-blade tip clearance. Experimental validation on an academic test rig demonstrates significant improvements. The ToA-PF method enhances clearance measurement accuracy by 77% compared to traditional methods under low and rapidly changing rotational speeds. Furthermore, the correction method for blade-by-blade tip clearance notably enhances measurement accuracy, particularly for the shortest blade, by over 50%. These proposed methods show promise in enhancing the accuracy and practicality of the BTC measurement method based on BTT, offering substantial value for turbine blade health monitoring and predictive maintenance applications.

Piano practice of China’s Cultural Revolution era and students’ musical creativity / La práctica de piano con composiciones de la era de la Revolución Cultural y la creatividad musical de los estudiantes

This paper describes the impact of the performance of piano pieces of the Cultural Revolution era with distinctive artistic features on the development of creative skills among students in the People’s Republic of China. The study used the SME academic test to measure the development of creative thinking. To measure the effect of practising piano on musical prowess, a control test (according to the currently accepted academic programme) was performed at the end of the study. The responses were given by students from three universities in the PRC. The total number of participants was 315 individuals. Based on the obtained results, it can be concluded that there is evidence of the effectiveness of piano practices that are based on musical compositions from the era of the Chinese Revolution, in terms of their positive impact. Small B groups showed 11.8% higher performance than the control group. Group B students experienced a positive impact on their level of creativity as a result of practising the piano. The average degree of creativity increased by 2.6%, while the high degree of creativity increased by 3.6%.

Developing a Word Family-Based Depth of Academic Word Knowledge Test

&lt;p style="text-align:justify"&gt;Despite the continued widespread use of the academic word list, there is a paucity of comprehensive and easily replicable tests which measure learners’ depth of knowledge of academic word list items. This paper outlines the development and initial validation of a test which measures multiple aspects of learners’ knowledge of academic vocabulary. The test comprises four sections – one productive knowledge section (sentence writing), and three receptive knowledge sections (collocations, synonyms, and L1 meaning). Each section includes 30 items selected from the academic word list, 10 of which are derived forms containing one or more affixes. The test was administered to 193 Japanese students studying at a public medical university in Japan. All four sections of the test showed a high level of internal consistency. In addition, the inter-rater reliability between the two different markers for the productive use (sentence writing) section was also moderately high. Furthermore, Rasch item analysis showed that the test items were well fitted to comprehensively measure learners’ knowledge of academic vocabulary. These encouraging initial results suggest that there may be merit in the test being used, evaluated, and possibly adapted in other EAP teaching and learning contexts.&lt;/p&gt;

Teacher effectiveness in English-medium instruction and students’ academic achievement: A value-added model in action

This study aimed to investigate the association between general science teachers’ effectiveness in teaching through English and students’ academic success in Debre Birhan City. In addition, it sought to determine which dimensions of English as a medium of instruction (EMI) accounted for the greatest variability. Furthermore, it examined whether demographic variables such as sex, qualification, and experience co-variated with students’ academic achievement (SAA). A non-experimental correlational design was employed. The study sample included 45 randomly selected teachers and 1575 students in 45 classrooms. A teacher effectiveness questionnaire and an academic achievement test were used as data collection tools implementing the principle of the value-added model. The findings revealed a strong relationship between teachers’ effectiveness in teaching science through English and SAA, with pedagogical knowledge being the highest contributor and experience co-variating with SAA. The unstandardized coefficient output also reveals that SAA increases by a certain percentage as every scale of EMI increases. The study recommends on-the-job training for EMI teachers. Additionally, experienced teachers should work in pairs with younger teachers and share fresh perspectives on teaching methods and effective language use. The introduction of EMI implementation policies is also recommended.

Development of Academic Achievement in Systemic Anatomy Course Through Flipped Classroom Teaching

Background and Aims: With the rapid development of modern information technology, the popularization of computers and networks not only changes the way of entertainment but also has a profound impact on the reform of teaching. With the diversification of knowledge acquisition methods, traditional teaching ideas and teaching methods have to face reform. The traditional infusing teaching method does not give play to the students' subjectivity, but also seriously blows the students' enthusiasm for learning. The flipped classroom teaching approach, on the contrary, pays more attention to the principal position of students, transforms the one-way transfer of knowledge in traditional teaching into a two-way interaction between teachers and students, to help students better understand and master knowledge, promotes the internalization of knowledge, and enhance students' learning initiative. The purposes of this study were; 1) To develop learning activities for the flipped classroom teaching approach in the Systemic anatomy course and 2) To compare academic achievement scores between pre-test and post-test using the flipped classroom teaching approach. And 3) To study the students’ satisfaction with the flipped classroom teaching approach in the Systemic anatomy course. Methodology: The sample consisted of 40 first-year students of Luzhou Vocational College of Medical Devices. In the first semester of 2023. Obtained by cluster random sampling technique. Research tools are used in lesson plans, academic achievement tests, and satisfaction questionnaires. In data analysis including percentages, means, standard deviations, and paired t-tests. Results: The results of the study were as follows; 1) The development of learning activities for the flipped classroom teaching approach in the Systemic anatomy course has an average suitability value for all plans equal to 4.31, which is at a high level. 2) Students who studied using flipped classroom teaching approach learning activities had higher academic achievement scores post-test than pre-test at a statistical significance of.05 and 3) Students who learned using the gamification teaching model had overall satisfaction at a high level. Conclusion: The Systemic Anatomy course's flipped classroom teaching strategy greatly increased students' academic progress and garnered high marks from them, according to the study. The post-test results were much higher than the pre-test results, and the learning activities that were devised were highly appropriate.

A Latecomer’s Advantage: The Attainments of Older Child Immigrants

Childhood immigrants arrive in the United States (U.S.) at different ages, each with a distinct set of skills. Previous research emphasizes the importance of early immigration in language acquisition and its subsequent effect on education and labor market outcomes. This study investigates whether migration timing has differential effects when considering other skills, specifically initial education quality. Using U.S. data of 322,328 childhood immigrants prior to 2018, we find that delayed childhood immigration from top-scoring countries in academic testing can mitigate the disadvantages associated with language acquisition. Our results suggest that children from topscoring, non-English-speaking countries appear to benefit most from later migration. Specifically, male immigrants gain an additional 2.57 years of U.S. education, while females gain 0.33 years. These additional years of education correspond to subsequent higher wages. Our study suggests a revaluation of policies, particularly regarding “late child immigrants” arriving from high-PISAscoring countries, as those individuals may achieve higher educational and income levels than previously anticipated.

SCHOOL CULTURAL PRACTICES AND LEARNERS ACADEMIC ACHIEVEMENT, IN PUBLIC PRIMARY SCHOOLS IN RWANDA: A CASE OF GASABO DISTRICT

This study investigates the impact of positive cultural practices in schools on the academic performance of learners in public primary schools in Gasabo District, Rwanda. It focuses on three key objectives: identifying the cultural practices upheld by school leaders, assessing the correlation between these practices and learners academic outcomes, and determining the overall influence of these practices on academic achievement. The research adopts both descriptive and correlational research designs, with data collected from a sample of 168 respondents through questionnaires and interviews. The data was analyzed using IBM SPSS Version 24, employing descriptive, correlational, and regression analyses to address the research questions. The findings reveal that 48.6% of schools do not prioritize cultural practices as a mean to enhance academic performance. However, 78.8% of respondents indicated that academic outcomes, including promotion, graduation rates, repetition rates, and test scores, are significantly influenced by the daily operations of schools. Additionally, 56.3% of respondents agreed that school norms, vision, goals, teacher-learner relationships, and assessment methods play a crucial role in academic success. Regression analysis demonstrated that school cultural practices account for 79.3% of the variance in academic performance (R-square), with a strong positive correlation (Pearsons coefficient = 0.916, p-value &lt; 0.01) between these practices and academic outcomes. The study concludes that the implementation of shared goals, school symbols, norms, and positive teacher-learner relationships can significantly enhance academic performance. It recommends that the Rwandan Ministry of Education and educational planners provide training on cultural practices to school leaders to further improve learner outcomes.

A Study on the Relationship Between Parents' Expectations and Junior Middle School Students' Academic Test Scores -- Taking English as an Example

In the currently prevalent “rat race” phenomenon, which is particularly acute in the field of education. When it comes to discussing the factors underlying the changes in middle school students' English academic achievements, numerous researchers have put forward their viewpoints from different perspectives. This paper summarizes four crucial dimensions that impact middle school students' English achievements and conducts a six-week teaching experiment based on these dimensions. Through the analysis of questionnaire surveys, interviews, and experimental comparisons, it is discovered that the factors influencing students' English achievements, ranked in order of importance from high to low, are: family rearing style, communication and emotional support between parents and children, parents' expectations, and family culture and values. However, while parental expectations have a direct and positive impact on adolescent children, they rank third among the major factors and have a relatively low impact. On the other hand, in the context of family rearing methods that are not suitable for children's development at this stage and incorrect family communication and emotional support, parents' expectations have indirect negative effects.

EXPERIMENTAL LABORATORY SET VIA INTERNET SYSTEM ON ELECTRICAL INSTRUMENT AND MEASUREMENT COURSE OF HIGHER VOCATIONAL CERTIFICATE PROGRAM OF RAJAMANGALA UNIVERSITY OF TECHNOLOGY ISAN, SAKON NAKHON CAMPUS

Development qualities, efficiency, and user satisfaction of the experimental laboratory set via internet system are electrical instrument and measurement course of the Higher Vocational Certificate Program of the Rajamangala University of Technology Isan, Sakon Nakhon campus. The research sample group consists of 21 first-year students in the Electronics Engineering Department, Higher Vocational Certificate Program, Rajamangala University of Technology Isan, Sakon Nakhon campus, and the choose a specific type. The research tools were the experimental laboratory set via internet system on electronic measurement tools course of Higher Vocational Certificate Program of Rajamangala University of Technology Isan, Sakon Nakhon campus., content and media production technical quality evaluation forms, academic achievement test and practice evaluation form, and user satisfaction evaluation form. Statistics used in this research were mathematical mean (x̄), standard deviation (SD), and percentage. The research results found that the experimental laboratory set via the internet system on electronic measurement tools course of Higher Vocational Certificate Program of Rajamangala University of Technology Isan, Sakon Nakhon campus have the content quality was good level (x̄ = 3.96, SD = 0.79) and the media production technical quality was good level (x̄ = 4.20, SD = 0.66).

Video Lectures With AI-Generated Instructors: Low Video Engagement, Same Performance as Human Instructors

Via AI video generators, it is possible to create educational videos with humanistic instructors by simply providing a script. The characteristics of video types and features of instructors in videos impact video engagement and, consequently, performance. This study aimed to compare the impact of human instructors and AI-generated instructors in video lectures on video engagement and academic performance. Additionally, the study aimed to examine students’ opinions on both types of videos. Convergent-parallel approach mixed method was used in this study. A total of 108 undergraduate students participated: 48 in the experimental group, 52 in the control group, and eight in the focus group. While the experimental group (AI-generated instructor) and control group (human instructor) watched 10 minutes of two videos each in two weeks, the students in the focus group watched both types of videos with human and AI-generated instructors. Data were collected through the Video Engagement Scale (VES) after the experimental process, and the Academic Performance Test as a pretest and posttest was administered in both groups. The findings of the experimental part revealed that learners’ video engagement was higher in the course with the human instructor compared to the course with the AI-generated instructor. However, the instructor type did not have a significant effect on academic performance. The results based on the qualitative part showed that students thought the AI-generated instructor caused distraction, discomfort, and disconnectedness. However, when the video lesson topic was interesting or when students focused on the video with the intention of learning, these feelings could be ignored. In conclusion, even in today’s conditions, there is no difference in performance between human and AI-generated instructors. As AI technology continues to develop, the difference in engagement is expected to disappear, and AI-generated instructors could be used effectively in video lectures.

Artificial Intelligence and Psychoanalysis: A New Concept of Research Methodology

The recent high performance of ChatGPT on several standardized academic tests has thrust the topic of artificial intelligence (AI) into the mainstream conversation about the future of education. As deep learning is poised to shift the teaching paradigm, it is essential to have a clear understanding of its effects on the current education system to ensure sustainable development and deployment of AI-driven technologies at schools and universities. Hence, AI behavior cannot be fully understood without human and social sciences. After the imaginary and symbolic registers, AI is the third register of identification. Therefore, AI extends the movement that is at work in the Lacanian interpretation of the mirror stage and Oedipus complex and which Latour’s reading helps us to clarify. From this point of view, I describe an AI system as a set of three contrasting forces: the human desire for identification, logic, and machinery. In the “Miscomputation and information” section, I show how this interpretative model improves our understanding of AI. Systematic research on psychoanalytic treatments has been limited by several factors, including a belief that clinical experience can demonstrate the effectiveness of psychoanalysis, rendering systematic research unnecessary, the view that psychoanalytic research would be difficult or impossible to accomplish, and a concern that research would distort the treatment being delivered.