Selection Of Students Research Articles

Measuring higher-order cognitive skills with multiple choice questions –potentials and pitfalls of Finnish teacher education entrance

This mixed methods study examines the structure of the multiple-choice exam for student selection in Finnish teacher education. Through qualitative content analysis, we categorized multiple-choice questions into items that assessed lower- and higher-order cognitive processes based on the Revised Bloom's Taxonomy. Exploratory and confirmatory factor analyses yielded four factors that represented lower- and higher-order cognitive processing skills and comprehension of empirical and theoretical items. These were associated with matriculation examination grades, especially with the average grade and the mother tongue grade. When developing future multiple-choice exams for admissions, we recommend emphasizing higher-order processing skills and the role of source materials.

A systematic exclusion induced by institutional ranking in engineering faculty hiring: Introducing a cycle of winners and losers.

This study empirically investigates exclusion induced by institutional ranking in engineering faculty hiring and introduces a cycle of winners and losers formed by privileging graduates of high-ranked institutions in the U.S. higher education system. We analyze and visualize academic origin (i.e., institutions faculty graduated from) and destination (i.e., institutions faculty are hired at) of 5,356 tenure-track faculty in four engineering disciplines of Chemical, Civil, Electrical, and Mechanical at the top 20 and bottom 20 of the top 100 engineering institutions according to the 2022 U.S. News & World Report. Our findings indicate that the hiring of engineering faculty in the U.S. higher education system is skewed in favor of graduates from high-ranked institutions, regardless of the discipline. Concerning each engineering discipline, 78% of electrical, 76% of chemical, 71% of mechanical, and 67% of civil engineering faculty of top 20 ranked institutions have academic origins in the top 20 ranked institutions. This hiring practice fosters inequalities by excluding qualified candidates and cementing the ranking system as the sole factor of academic quality. We bring attention to the pitfalls stemming from the exclusion in the U.S. higher education system, including (1) financial resources, (2) faculty and student resources, (3) selectivity and self-selection, and (4) geography. The cascading effect of the ranking practice is the unintended consequence of inaugurating a virtuous and vicious cycle, which creates a cycle of winners and losers that is difficult to break. High-ranked institutions easily dominate and maintain their ascendancy status in the ranking system as benefactors of the virtuous cycle. Low-ranked institutions are entrapped in the vicious cycle that makes it nearly impossible to (1) attract and retain both students and faculty, (2) secure external funding, (3) obtain resources for new programs, and (4) advance engineering research. Unless the U.S. higher education system is intent on squandering talent, confirming the belief that diversity is symbolic, and cementing the ranking system as the sole factor of academic quality, we recommend faculty hiring beyond the standard sociodemographic indicators and academic origins in hiring decisions. A proactive, open-minded, and neutral approach to the faculty selection process void of decision-making based on affinity should be the central tenet of the selection committee.

When and why do medical students drop out of extracurricular longitudinal general practice tracks? A cross-sectional study from two German medical faculties

ObjectivesTo explore when and why undergraduate medical students drop out of longitudinal extracurricular general practice (GP) tracks and to describe their future career plans.DesignCross-sectional online survey and descriptive analysis of...

The Effect of Home Economics Instruction Applying Flipped and Problem-Based Learning on Middle-School Students’ Metacognition Skill

The purpose of this study is to identify the effect of Home Economics Instruction applying Flipped and Problem-Based Learning (FPBL) on Korean middle-school students’ metacognition skill. The study uses a prepost design test of the same group. There were 151 participants (77 male and 74 female) who were middleschool students in the third grade. Two hours of classes on ‘Food Selection and Storage’ were given per week for three weeks – a total of six hours. Analysis using the <i>t</i>-test revealed a statistically significant difference between the pre-test and the post-test, supporting the conclusion that participating in the class improved the metacognition, food selection, and storage behavior scores of the middle-school students. All area scores and overall averages of metacognitive sub-elements such as planning, monitoring, regulation, and evaluation also improved after taking FPBL classes. From the results of this study, Home Economics Instruction applying FPBL is an effective teaching method for improving middle-school students’ metacognition.

URGENSI INTELIGENSI BESERTA AFIRMASI BAGI PENDIDIKAN DAN PEMBELAJARAN

Intelligence is a psychological attribute that has a very important role in the educational process, especially science and practice of Guidance and Counseling. The results of intelligence measurements are a picture of previous education that has been achieved, and can also be a predictor (forecasting tool) to the results of education in the future, especially with regard to the selection of prospective students or students who exceed the limits of school or college. But it must be realized that not all intelligence tests are suitable to be used as a tool to predict because there are many factors that can affect the suitability of the application. It must also be realized in predicting a success in learning that learning itself is not merely the utilization of potential abilities (intelligence), but there are still many factors that help determine the outcome of the learning process. Success in learning can reflect intelligence or is a reflection of assessing a student's intelligence capacity. The higher a person's level of intelligence, the more likely the higher the success of learning achieved. Basically intelligence has a very big relationship to the success of the person in learning something. Therefore, intelligence is very related to the learning ability of students in school or on campus.Keywords: Intelligence, Education, Learning

Penerapan Metode Multi-Objective Optimization on the Basic of Ratio Analysis (MOORA) dalam Keputusan Penerimaan Siswa Baru

This research was made so that the school can easily select new students who are running as students in a school. This selection is done based on the criteria that have been determined by the school. To solve this problem, a decision support system is needed using the Multi-Objective Optimization Method on The Basic of Ratio Analysis (MOORA). this method is also quite easy to use and the results are good by obtaining the best value of 0.2296 with alternative A1 and followed by alternative A5 with a preference value of 0.1383. So that the decision support system by applying the MOORA method can solve problems in the selection of new students who are accepted or declared graduated with a systematic and precise selection. The MOORA method can also be used in people who really need it

Decision support system for the selection of students for Erasmus+ short-term mobility

PurposeThe current student selection process for short-term mobility actions under the Erasmus + program (i.e. intensive programs and blended intensive programs) is based exclusively on the students' order of enrolment and their grades. This study offers an alternative approach using the analytic hierarchy process based on a four-layer model that collects information about the specificities of each project and the profile of the students and also promotes greater inclusion and homogenization of the project teams.Design/methodology/approachA decision support system was built by decomposing it into three stages: the predesign stage, in which the problem is characterized, and the user requirements are identified; the design stage, in which the models, the database and the interfaces are formulated; and the field stage, in which six test scenarios were built to validate the proposed solution.FindingsThe results show that this model can be applied with various selection criteria among students and consider both their hard and soft skills. It can also be applied to help build teams in which the students' knowledge is aligned with the technical skills required by the projects.Originality/valueThe proposed approach is innovative in that it responds to the emerging challenge of short-term European mobility programs that aim to involve students with multidisciplinary competencies. The solution considers both hard and soft skills in the selection of students, which allows changing the student selection paradigm and obtaining potentially more homogeneous multicultural teams with greater learning potential.

Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study

The study investigates the efficacy of new features introduced to the selection process for medical school at the University of New South Wales, Australia: (1) considering the relative ranks rather than scores of the Undergraduate Medicine and Health Sciences Admission Test and Australian Tertiary Admission Rank; (2) structured interview focusing on interpersonal interaction and concerns should the applicants become students; and (3) embracing interviewers’ diverse perspectives. Data from 5 cohorts of students were analyzed, comparing outcomes of the second year in the medicine program of 4 cohorts of the old selection process and 1 of the new process. The main analysis comprised multiple linear regression models for predicting academic, clinical, and professional outcomes, by section tools and demographic variables. Selection interview marks from the new interview (512 applicants, 2 interviewers each) were analyzed for inter-rater reliability, which identified a high level of agreement (kappa=0.639). No such analysis was possible for the old interview since it required interviewers to reach a consensus. Multivariate linear regression models utilizing outcomes for 5 cohorts (N=905) revealed that the new selection process was much more effective in predicting academic and clinical achievement in the program (R2=9.4%–17.8% vs. R2=1.5%–8.4%). The results suggest that the medical student selection process can be significantly enhanced by employing a non-compensatory selection algorithm; and using a structured interview focusing on interpersonal interaction and concerns should the applicants become students; as well as embracing interviewers’ diverse perspectives.

Decision Support System For Selecting The Best Practical Work Students Using MOORA Method

This research aims to solve the problem of selecting the best practical work students at the Politeknik Bisnis Indonesia. The current selection of the best practical work students at PBI does not yet use a decision support system approach. This problem is solved by building a Decision Support System using Multi-Objective Optimization based on Ratio Analysis (MOORA) method. The criteria used in this DSS consist of discipline, teamwork, skills, quality of work, and attendance. As for the results of data processing from this study, the three best alternative data were obtained, namely alternative Vivi (A6) as the 1st best Practical Work Students with a score of Yi = 36.5954, Hafiz (A1) as the 2nd best Practical Work Students with a score of Yi = 34.5339, Cahaya (A3) as the 3rd best PKL student with a score of Yi = 33.4767. Through this decision support system that has been built, the selection of the best practical work students can be made quickly and effectively.

A Systematic Study of the Literature on Career Guidance Expert Systems for Students: Implications for ODL

The continual evolution of employment opportunities in the present industrial era has raised the need for career-long expert advice. Similar to other fields, thankfully technology has come to our rescue in the area of career guidance also. This paper presents a systematic review of Expert Systems (ES) developed for career guidance, course selection and evaluation of students in the past ten years. The popular research databases Google Scholar and Science Direct were used for obtaining the relevant research papers through broad keywords. The keywords were refined to identify the articles related to rule-based, case-based and fuzzy logic-based ES used for career guidance. A total of twenty-five peer-reviewed relevant articles with full-text available online was selected for the final study. In order to avoid duplicity, technical reports and unreferenced literature were excluded. The review identifies the relatively high weight given by the researchers to rule-based systems owing to their simplicity and broad applicability. However, the relative merits and demerits of rule-based, case-based and fuzzy logic-based ES are highly dependent on the field of application. Nevertheless, ES find wide applications in the area of career guidance and have the potential to enhance the career guidance accessibility of the most remote students.

Sistem Penunjang Keputusan Penerimaan Siswa Baru Berprestasi Di SMP IT Surakarta Menggunakan Metode Nearest Neighbor Dan Simple Additive Weighting

SMP IT Nur Hidayah Surakarta, was established in 2004/2005 academic year. SMP IT Nur Hidayah has been graduated 3 generation of graduation, on the academic year of 2006/2007, 2007/2008 and 2008/2009. In the new student admission program there is an acceptance limit for students who are eligible for scholarships. The criteria used in the selection process include: average grades of report cards, written tests, parents' income and achievements. In decision new students, the school wants quality selection results by predicting new prospective students and then decide new students. The purpose of this study was to design a decision support system for new students using the Nearest Neighbor (NN) and Simple Additive Weighting (SAW) methods. This method was chosen because it is able to carry out a prediction process and a ranking process to determine the best alternative. The technique used in this research is observation, interview and literature study. In the design of this system is made with Context Diagram, HIPO, DAD, relations between tables and database design. The application is made using the PHP programming language and the database uses My SQL. The final results are in the form of student data reports, prediction reports, selection reports and reports on the best selection results. System testing is done by testing the functionality which shows the accepted results and the validity test which shows the valid results. The results of system testing with the MAPE test showed an accuracy of 88.7%.

An Innovative Hybrid Multi-Criteria Decision-Making Approach under Picture Fuzzy Information

These days, multi-criteria decision-making (MCDM) approaches play a vital role in making decisions considering multiple criteria. Among these approaches, the picture fuzzy soft set model is emerging as a powerful mathematical tool for handling various kinds of uncertainties in complex real-life MCDM situations because it is a combination of two efficient mathematical tools, namely, picture fuzzy sets and soft sets. However, the picture fuzzy soft set model is deficient; that is, it fails to tackle information symmetrically in a bipolar soft environment. To overcome this difficulty, in this paper, a model named picture fuzzy bipolar soft sets (PRFBSSs, for short) is proposed, which is a natural hybridization of two models, namely, picture fuzzy sets and bipolar soft sets. An example discussing the selection of students for a scholarship is added to illustrate the initiated model. Some novel properties of PRFBSSs such as sub-set, super-set, equality, complement, relative null and absolute PRFBSSs, extended intersection and union, and restricted intersection and union are investigated. Moreover, two fundamental operations of PRFBSSs, namely, the AND and OR operations, are studied. Thereafter, some new results (De Morgan’s law, commutativity, associativity, and distributivity) related to these proposed notions are investigated and explained through corresponding numerical examples. An algorithm is developed to deal with uncertain information in the PRFBSS environment. To show the efficacy and applicability of the initiated technique, a descriptive numerical example regarding the selection of the best graphic designer is explored under PRFBSSs. In the end, concerning both qualitative and quantitative perspectives, a detailed comparative analysis of the initiated model with certain existing models is provided.

Factors for Poor Performance in Religious Education in Secondary Schools: A Case of Secondary Schools in Tungi Ward, Morogoro Municipality

This study was designed to establish factors for poor performance in religious education in Secondary Schools: A case of Secondary Schools in Tungi Ward, Morogoro Municipality. Specifically, the study aimed at establishing school- and student-related factors for poor performance in religious education in Secondary Schools in Tungi Ward, Morogoro Municipality. The targeted population for the study comprised heads of schools, teachers, and students from three secondary schools in the Tungi Ward, namely Tubuyu Secondary School, Charlotte Secondary School, and La Miriam Secondary School. The study used a simple random sampling technique in the selection of teachers and students and a purposive sampling technique in the selection of heads of schools, totalising 65 respondents. The data were collected through questionnaires, interviews, and focus group discussions. The analysis was done by using content analysis and descriptive statistics, data presentation was done by using explanatory sequential. The findings revealed that school-related factors that cause poor performance in RE in secondary schools include lack of qualified religious teachers, unavailability of teaching and learning resources, teachers’ pedagogical and assessment skills, teacher-student ratio, and language of instruction. Government-related factors that cause poor performance in RE in secondary schools include an over-loaded curriculum, lack of motivation toward teachers, lack of capacity-building programs, and under-qualified teachers; and student-related factors include attitudes towards learning, family background, and peer influence. The study recommends the following, school authorities devote special budgets to improving their libraries; Government needs to step up its support financially and materially to schools so as to help them improve facilities in order to ensure there is better academic performance; parents need to pay special attention to the academic performance of their children

College competitiveness and medical school exam performance

BackgroundIn medical school, students are tested through periodic USMLE Step 1 and 2 examinations before obtaining a medical license. Traditional predictors of medical school performance include MCAT scores, undergraduate grades, and undergraduate institutional selectivity. Prior studies indicate that admissions committees might unfairly discriminate against applicants who graduated from less competitive universities. However, there is limited literature to determine whether those who attended competitive colleges perform better on USMLE Step 1 and 2 examinations.ObjectiveThe purpose of our study is to determine if students who attended competitive undergraduate colleges outperform those who did not on medical school benchmarks.MethodsWe defined a Competitive College as having greater than 10% of its student body scoring 1400 or higher (on a 1600 scale) on the SAT. If this criteria was not met, colleges would be categorized as Non-Competitive. Descriptive statistics and unpaired t-tests were calculated to analyze average test scores on the MCAT, Phase 1 NBME, USMLE Step 1, Phase 2 NBME, and USMLE Step 2.ResultsOur findings suggest there are no statistically significant differences between students who do or do not attend competitive undergraduate colleges on these medical school benchmark examinations following the MCAT.ConclusionAdmissions committees should use this data to aid in their student selection as our research indicates that institutional selectivity accurately predicts MCAT scores, but not performance on standardized medical school examinations once admitted.

Prevalence and description of digital device use among preschool children: A cross-sectional study in Kota Setar District, Kedah.

Digital device helps children enhance academic, cognitive and psychomotor skills. However, prolonged use causes physical inactivity, poor interpersonal skills and communication problems. Information on digital device use among young children in Malaysia is currently limited. Hence, this study aimed to determine the prevalence of digital device utilisation among preschool children in Kota Setar District, Kedah. A cross-sectional study at government preschools in Kota Setar District was conducted from February to April 2020. Selection of preschools and students was done using multistage simple randomisation. A self-administered questionnaire containing demographic and digital device use details was filled by parents. The prevalence of digital device use among preschool children was 95.9% and mostly used smartphones (94.2%). Most children (95%) did not own the device, and usage was under supervision (95.7%). The reason for supervision was to prevent exposure to inappropriate content (70.5%). The common reasons for allowing digital device use were for educational (37.4%) and entertainment purposes (36%) through videos (30.9%) and games (30.2%). Approximately 21.5% and 50.3% of the children spent more than 1 and 2 hours on digital devices during weekdays and weekends, respectively. The prevalence of digital device use among the preschool children in Kota Setar District was very high. Most of them used digital devices for educational and entertainment purposes under parental supervision. However, some exceeded the recommended screen time on weekends. These findings could promote awareness of digital device use among young children and help design public health awareness programmes and future policies.

Liberalisasi Penjaringan Mahasiswa Baru di Perguruan Tinggi Keagamaan Islam Negeri: Tantangan dan Peluang

The government seeks to liberalize higher education by encouraging the realization of higher education management autonomy. To be independent, universities carry out liberalization through the selection of new students. The emergence of the phenomenon of several allegations of new student admissions provides opportunities for liberalization policies in recruiting new students that have excesses that need to be studied for opportunities and challenges for PTKIN, which is identical to the mission of da'wah. For this reason, it seeks to discuss the liberalization policy in the selection of new students in terms of (1) the forms of legal policy; (2) the challenges of negative excess (3) and the opportunities for advancement for PTKIN. The research uses qualitative methods, through a literature study approach, by collecting secondary data in the form of relevant documents to answer research questions. The results of the study indicate that (1) the Indonesian government has liberalized higher education, in the form of a higher education autonomy policy, in which each institution is given wider authority to obtain funding from the public through the selection of new students. (2) In practice, liberalization in the selection of new students poses negative excess challenges: Increasing education funding by the poor; being stuck in the material-oriented corporate paradigm; Falling into the behavior of corruption, collusion, and nepotism. (3) Liberalization provides opportunities for progress for PTKIN to optimize the role of education financing by the community; The diversity of PTKIN student backgrounds; the Opportunity to build a humanist and fair PTKIN. Practically, the three points of the research findings imply that in implementing the new student recruitment policy, PTKIN can direct the policy to build PTKIN priorities that are humanist and just by avoiding the number of negative excesses that are not in line with PTKIN's ideology as a da'wah institution.

Evaluating School Priorities for Equal Opportunity in Admission to Schools

ABSTRACT Schools’ priorities in student selection constitute the basis for fairness in school admissions. We study the case where schools are active strategic players that rank their applicants in terms of priorities. A methodological framework is developed to examine the impact of the variation in the admission settings on the equality of opportunity in access to high-quality schools. The school’s priorities are formulated following a Multi-Attribute Decision Analysis (MADA) approach with several scenarios including geographic, family, academic, and socioeconomic variables. The matching is simulated using student preferences, multiple assignment algorithms, varying school capacities, and changing priority profiles. The Human Opportunity Index (HOI) logistic regression approach is used to examine how far from, or how close the admission is to being an equitable assignment, i.e., one that gives equal opportunities to children with different backgrounds. The analysis is based on choice admission data from a large specialized (magnet) middle school program in Florida. The results suggest that how the school priority is designed slightly affects the equality of opportunity. The second impact is due to the algorithm used to perform the selection. The availability of places in high-quality schools has a big impact and is tightly correlated with the parents’ satisfaction with their most preferred school choices.

The added value of signal detection theory as a method in evidence-informed decision-making in higher education: A demonstration

Signal Detection Theory (SDT) is rarely used in higher education, yet has much potential in informing decision-making. In this methodological paper, we describe the potential of SDT for different higher education contexts and demonstrate its practical application. Both the commonly used regression analyses and SDT analyses provide information on the accuracy of a predictor, and thus which instrument(s) to use. SDT analyses, in addition, provide information on the effects of setting specific cut-off scores on outcomes of interest. SDT provides the sensitivity and specificity information for the chosen instrument(s) at specific cut-off scores (criteria in SDT). This allows for evidence-informed, deliberate choice of cut-off scores to steer toward desired outcomes. Depending on how undesirable false positives and false negatives are considered in a specific situation, a lower or higher cut-off score can be deemed adequate. Using SDT analyses in our example, we demonstrate how to use the results to optimize “real-life” student selection. However, selection is only one of many decision-making practices where SDT is applicable and valuable. We outline some of the areas within higher education decision-making and quality assurance, where SDT can be applied to answer specific questions and optimize decision-making.

The impact of volunteering with a student-run free clinic on medical student specialty selection

BackgroundThe shortage of primary care physicians in the United States is expected to grow to 17,800–48,000 physicians by 2034. Student Run Free Clinics are an increasingly popular component of medical schools and may provide an avenue for increasing medical student interest in primary care specialties. However, there is limited research on the impact of Student Run Free Clinics on medical student specialty choice. This investigation sought to determine whether volunteering with the Interprofessional Community Clinic (ICC), the Student Run Free Clinic associated with Chicago Medical School, was associated with an increased likelihood of matching into primary care specialties. Secondarily, the authors investigated associations between volunteering and matching into family practice. Finally, the authors explored associations between volunteering and the competitiveness of specialty choice.MethodsThis retrospective review utilized data on medical school graduates from 2015 – 2021 including their matched specialties, the number of ICC shifts they volunteered for, and whether they held an ICC leadership position (executive officers). Primary care specialties were defined as internal medicine, family practice, pediatrics, or combined internal medicine/pediatrics. Residency fill rate was used as a proxy for competitiveness.ResultsThis analysis included 506 medical students (254 ICC volunteers and 252 non-volunteers). Among ICC volunteers, 47.2% matched into a primary care specialty compared to 36.5% of non-volunteers (RR 1.29, 95% CI 1.05–1.59). Each additional shift worked at the ICC was correlated with increased odds of matching into family practice by a factor of 1.042 (95% CI 1.005–1.079).ConclusionsMedical students who volunteered with the ICC were more likely to match into primary care residencies. Students who volunteered more frequently were more likely to match into family practice. Further investigation is warranted to determine whether these associations are causative and could thus be leveraged to encourage medical students to pursue primary care careers.

Student Selection Process for Undergraduate Medical Programme Amid the COVID-19 Pandemic: Lessons Learned and Future Directions for Universiti Putra Malaysia

Student Selection Process for Undergraduate Medical Programme Amid the COVID-19 Pandemic: Lessons Learned and Future Directions for Universiti Putra Malaysia