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Johargy, Dr Ayman, Dr Pushpamala Ramaiah, and Dr Ibtesam Nomani Lamia Ahmed Elsayed Grace Lindsey. "Student Nurses Academic Performance- Multidimensional Constructs." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 818–22. http://dx.doi.org/10.31142/ijtsrd23144.
Laxmi, A. Sindura, and Sandeep Patil. "The Student Performance Monitoring Using ARM9." International Journal of Scientific Research 1, no. 7 (June 1, 2012): 66–69. http://dx.doi.org/10.15373/22778179/dec2012/27.
Young people was active users of the information technology, especially internet. Even some of them tend to make the internet as a medium of the main support daily activities. These study indicate that internet use among young people, especially college student tend to have a model of its own behavior, making it attractive for further investigation. These study focus on the influence of perceived enjoyment as variables anticedent in the Technology Acceptance Model (TAM). The respondents of these study were college student as internet users in Yogyakarta, the province is considering a student city. These study conducted on 130 respondents. According to the structural analysis with SEM method, shows that perceive enjoyment has a role as anticedent variable on TAM, because those variable has significant effects on variables in technology acceptance model.
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Shetty, Isha D., Dipshi Shetty, and Sneha Roundhal. "Student Performance Prediction." International Journal of Computer Applications Technology and Research 8, no. 5 (April 24, 2019): 157–60. http://dx.doi.org/10.7753/ijcatr0805.1003.
Setemen, K., and I. K. Purnamawan. "Student performance assessment strategies by involving peer students." Journal of Physics: Conference Series 1810, no. 1 (March 1, 2021): 012064. http://dx.doi.org/10.1088/1742-6596/1810/1/012064.
The main goal of this study was to investigate the influence of teacherstudent interaction on academic performance of the students. Hundred participants (50 teachers and 50 students) were selected through purposive sampling technique to conduct this research. Teacher and student feedback were measured by using the Questionnaire on Teacher Interaction (QTI) as well as students’ academic performance was calculated by using last year grade point average (GPA) of each student. Pearson product moment correlation was used which indicated a positive significant correlation (r = 0.70, p < 0.05) between teacher-student interaction and academic performance of the students. The findings indicated the importance of teacher-student relationships to attain academic success of the students. The results suggest providing appropriate academic resources and aids for the teachers to meet the individual needs of their students.
Dhaka Univ. J. Biol. Sci. 30(1): 87-93, 2021 (January)
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Foos, Paul W. "Effects of Student-Written Questions on Student Test Performance." Teaching of Psychology 16, no. 2 (April 1989): 77–78. http://dx.doi.org/10.1207/s15328023top1602_10.
Effects of student-written test questions on student test performance were examined in an Introductory Psychology class. Before each of three tests, randomly assigned students wrote essay questions, multiple-choice questions, or no questions. All tests contained essay and multiple-choice items but no questions written by students. Question writers performed significantly better than nonwriters on the first two tests; the difference on the third test was marginally significant. No differences were found between students who wrote essay and those who wrote multiple-choice questions. Question writing appears to be an effective study technique.
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PURCARU, Monica A. P. "ASPECTS REGARDING THE LEVEL OF PERFORMANCE IN MATHEMATICS." Review of the Air Force Academy 18, no. 2 (January 22, 2021): 57–62. http://dx.doi.org/10.19062/1842-9238.2020.18.2.6.
In the present paper addressing the issue of advanced performance in mathematics, we seek to answer to the following study questions: “What are the main factors that lead to the achievement of advanced performance?”; “Which is the profile of the teacher able to train the Olympic students in Mathematics?”; “Why do teachers want for their students to achieve advanced performance in mathematics?”; “Why do the students want to reach a high degree of performance in Mathematics?”; “What difficulties could significantly impede on student progress?”; “What is the connection between enthusiasm and advanced performance in Mathematics?”; “ Why does an Olympic student participate in competitions?”.
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Liu, Chen-Chung, Gwo-Dong Chen, Chin-Yeh Wang, and Ching-Fang Lu. "Student Performance Assessment Using Bayesian Network and Web Portfolios." Journal of Educational Computing Research 27, no. 4 (December 2002): 437–69. http://dx.doi.org/10.2190/el2a-tqf1-pyvm-n51v.
Web-based curriculum development allows students to develop their learning portfolio and interact with peers on a Web learning system. This system contains Web portfolios that record in detail students' learning activities, peer interaction, and knowledge progress. However, teachers cannot easily diagnose students' learning processes and regulate effective strategies according to student activity performance without the model of activity performance on Web learning systems. This study proposes a novel methodology that employs Bayesian network software to assist teachers in efficiently deriving and utilizing the student model of activity performance from Web portfolios in an online manner. Teachers can assess and diagnose performances with the model of learning activity on Web learning systems. The model of activity performance also allows teachers to manage various activity performances in Web learning systems so that desired strategies can be achieved to promote learning effectiveness.
Moses, R. "Improving student performance." Tshwane University of Technology, 2013. http://encore.tut.ac.za/iii/cpro/DigitalItemViewPage.external?sp=1001657.
Bellman, Markus, and Gustaf Blidholm. "Student performance drivers : An analysis of the declining performance of Swedish middle school students." Thesis, KTH, Optimeringslära och systemteori, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189028.
The PISA reports presented between 2000 and 2013 display a sustained decline in the mathematics proficiency of Swedish middle school students. The latest OECD reports suggest that the downward trend is still present, whereby the aim of this thesis is to investigate its underlying causes. Can the decline be deduced from the poor performance of specific Swedish municipalities with significantly worse results than others? By analyzing the current situation in Swedish education from a national standpoint, the intention is to derive the main factors for good overall math performance in middle school within a municipality. Moreover, the thesis aims to identify areas of possible enhancement within the Swedish education system on a municipal as well as a national level, by analyzing how political financial decisions and society as a whole factor into student performance. Finally, the impact of education on aspects of macroeconomics is analyzed. It is arbitrated that several factors controllable by the government have significant impact on the average math performance of students in a Swedish municipality. The results from the analysis indicate that governmental expenditures are better spent on quality of teaching than on the quantity of teachers present. PISA-rapporterna publicerade mellan 2000 och 2013 påvisar en tydlig nedåtgående trend i matematikresultat f ̈or svenska högstadieelever. Nya OECD-rapporter tyder på att trenden alltjämt kvarstår. Denna uppsats ämnar undersöka vilka anledningar som ligger bakom den negativa utvecklingen. Kan nedgången härledas ur skolresultat i specifika kommuner med sämre resultat än andra? Den nuvarande situationen i den svenska skolan analyseras ur ett nationellt perspektiv, där kommuner jämförs med varandra. Målet är att undersöka vilka huvudfaktorer som leder till bra skolresultat i en kommun. Vidare är ett mål att identifiera hur det svenska skolsystemet kan förbättras på både kommunal och nationell nivå med hjälp av politiska finansieringsbeslut, samt att analysera vilka faktorer hos samhället i stort som påverkar skolresultaten. Slutligen analyseras utbildningens påverkan på aspekter inom nationalekonomi ur ett makroperspektiv. Slutsatsen dras att flera påverkbara faktorer har signifikant inflytande på elevers genomsnittliga matematikprestation i en kommun. Dessutom konstateras att statliga utgifter skulle göra mer nytta om man valde att satsa på lärarnas kvalitet istället för att satsa på ett ökat antal lärare.
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Lunsford, Garrett P. "Environmental effects on student performance /." Available to subscribers only, 2009. http://proquest.umi.com/pqdweb?did=1885755991&sid=4&Fmt=2&clientId=1509&RQT=309&VName=PQD.
AN ABSTRACT OF THE THESIS OF Garrett P. Lunsford, for the Masters degree in Architecture, presented on July 10th 2009, at Southern Illinois University Carbondale. TITLE: ENVIRONMENTAL EFFECTS ON STUDENT PERFORMANCE MAJOR PROFESSOR: Dr. Walter Wendler With the increasing concern for sub par student performance in America, it has become more vital than ever for designers to create optimal learning environments. Student performance is significantly dependent on the quality of teaching as well as the pupil-instructor relationship. However, it is rare for even our best instructors to receive adequate performance from their students when teaching in poor environments. Research for more than 30 years has displayed explicit correlation between physical characteristics of school buildings and educational outcomes. These physical characteristics include lighting, acoustics, thermal control, indoor air quality, as well as class size. By taking each of these factors into consideration, architects can produce settings that do not hinder student performance. Better educated children today will make the world a smarter, improved, more sustainable environment tomorrow.
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Edwards, Nicole C. "School facilities and student achievement student perspectives on the connection between the urban learning environment and student motivation and performance /." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1164663224.
Wong, Chan Pik-Yuen. "Human factors in performance assessment : the assessment of practicum performance in social work." Thesis, University of Bristol, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369110.
Haskell, Loretta Murray. "Student Performance of a Library-Related Task." Thesis, North Texas State University, 1986. https://digital.library.unt.edu/ark:/67531/metadc330802/.
The high school research paper is a task which consumes instructional time, requires considerable student effort, and places a high demand on school library resources. Little research has been conducted on how students accomplish this task. Academic task research indicates that in classrooms, tasks are defined by students in terms of (a) the nature of the products the teacher will accept and (b) the operations allowed and the resources available. Here the product is the research paper; the resources available include those found in the school library. The purpose of this study was to determine what strategies students use to perform the library-related task.
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Wei, Xin. "Accountability stringency, incentives and student performance /." May be available electronically:, 2008. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.
Clancy, Diane M. "The effects of student accountability on student performance and self-efficacy." [Bloomington, Ind.] : Indiana University, 2004. http://wwwlib.umi.com/dissertations/fullcit/3173527.
Thesis (Ed.D.)--Indiana University, Dept. of Educational Leadership, 2004. Source: Dissertation Abstracts International, Volume: 66-04, Section: A, page: 1278. Director: Terrence C. Mason. "Title from dissertation home page (viewed on Nov. 22, 2006)."
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Winton, Terry W. "Student and Teacher Perceptions of Standards-based Grading and Student Performance." Thesis, Lindenwood University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3728021.
Assessing student learning has been part of education since the beginning of formalized schooling. Developments at the national, state, and local level have led to grading reforms over the past quarter century. The purpose of this study was to explore students’ and teachers’ perceptions of standards-based grading to determine if there was a significant difference on standardized tests scores between students graded using standards-based grading and students graded using traditional grading. Teachers and students from one Missouri high school were interviewed to determine their perceptions about standards-based grading. A stratified sample was utilized to select interviewees. Artifacts from the district were analyzed to determine the process in the implementation of standards-based grading. Quantitative data were obtained from the Missouri Department of Elementary and Secondary Education to compare the Missouri Assessment Performance (MAP) Index scores and means on end-of-course exams from the participating high school with Missouri students. A t-test was utilized to determine the difference between the two means. The data revealed teachers’ perceptions of standards-based grading were varied, with only two teachers who preferred standards-based grading. Student perceptions were more positive than those of teachers, with 50% of students who were interviewed preferring standards-based grading. Quantitative data revealed no statistically significant difference between the means on end-of-course exams of students assessed with standards-based grading and students assessed with traditional grading in five of the eight subject areas studied.
Association, New York State School Boards. Gauging student performance. Albany, N.Y. (119 Washington Ave., Albany 12210): New York State School Boards Association, 1989.
Flach, Tracey K. Engaging students through performance assessment: Creating performance tasks to monitor student learning. Englewood, Colo: Lead + Learn Press, 2011.
National Study of School Evaluation. School improvement: Focusing on student performance. Edited by Steadman David G and Fitzpatrick Kathleen Ann 1950-. Schaumburg, IL (1699 E. Woodfield Rd., Suite 406, Schaumburg 60173): National Study of School Evaluation, 1995.
National Study of School Evaluation. School improvement: Focusing on student performance. Schaumburg, IL (1699 E. Woodfield Rd., Ste. 406, Schaumburg 60173): NSSE, 1997.
Miles, Myers, Spalding Elizabeth 1951-, and National Council of Teachers of English., eds. Standards exemplar series: Assessing student performance. Urbana, IL: National Council of Teachers of English, 1997.
Watson, Jane, Kim Beswick, and Natalie Brown. "Student Performance." In Educational Research and Professional Learning in Changing Times, 61–68. Rotterdam: SensePublishers, 2012. http://dx.doi.org/10.1007/978-94-6091-945-9_5.
Mavis, Brian. "Assessing Student Performance." In An Introduction to Medical Teaching, 209–41. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9066-6_15.
Mavis, Brian. "Assessing Student Performance." In An Introduction to Medical Teaching, 143–78. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-3641-4_11.
Magolda, Peter M. "Nonrational Classroom Performance." In Rituals and Student Identity in Education, 73–89. New York: Palgrave Macmillan US, 2011. http://dx.doi.org/10.1057/9780230117167_4.
Salili, Farideh, Chi-yue Chiu, and Simon Lai. "The Influence of Culture and Context on Students’ Motivational Orientation and Performance." In Student Motivation, 221–47. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1273-8_11.
Urdan, Tim. "Contextual Influences on Motivation and Performance: An Examination of Achievement Goal Structures." In Student Motivation, 171–201. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1273-8_9.
Swathi, Monagari, K. L. S. Soujanya, and R. Suhasini. "Review on Predicting Student Performance." In Lecture Notes in Electrical Engineering, 1323–30. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7961-5_120.
Orozco, Walter, Miguel Ángel Rodríguez-García, and Alberto Fernández. "Estimating Expected Student Academic Performance." In Advances in Intelligent Systems and Computing, 121–31. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57799-5_13.
Smith, Barbara. "Student and Staff Performance Reviews." In A Charter School Principal’s Story, 61–66. Rotterdam: SensePublishers, 2017. http://dx.doi.org/10.1007/978-94-6351-218-3_15.
Soujanya, K. L. S., Challa MadhaviLatha, M. Swathi, Ch Mallikarjuna Rao, and Sridevi Sakhamuri. "Student Performance Assessment Using AI." In Cybernetics, Cognition and Machine Learning Applications, 185–93. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1484-3_21.
Тези доповідей конференцій з теми "Student performance":
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Bessette, Amanda, Vitalis Okafor, and Beshoy Morkos. "Correlating Student Motivation to Course Performance in Capstone Design." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-35506.
This paper presents the preliminary results of a motivational study of students enrolled in their capstone design course during their senior year in mechanical engineering at the Florida Institute of Technology. Student teams are assigned a project and teams are tasked with completing a design project over a one-year (2 semesters) span. Data is collected during the beginning of the fall semester and during the end of the spring semester. Two methods were used to collect the data of the class. A live interview was conducted for each of the capstone teams. Within this interview, a range of questions are asked to facilitate an understanding of what motivates the student. An adaptation of the Motivated Learning Strategies Questionnaire (MSLQ) survey instrument was also administered to the students to collect quantitative data. The MSLQ framework divides the instruments into two sets of questions to address motivation and learning. Motivation is comprised of three factors: test anxiety, self-efficacy, and intrinsic value. Statistical analysis is performed on the quantitative data to determine significance or correlation between student motivation and performance. Performance is measured through the student’s grade (evaluated by instructor) and peer evaluation (evaluated by team). The analysis is performed through segmenting the sample into international versus domestic, and males versus females; to identify any differences in motivation between the groups. Results indicate there are differences between international and domestic students along all motivational factors. Further, differences are identified between males and females for intrinsic anxiety motivational factors.
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Holmes-Smith, Philip. "Communicating student performance data to school teachers." In Statistics Education and the Communication of Statistics. International Association for Statistical Education, 2005. http://dx.doi.org/10.52041/srap.05304.
The results from national studies of student ability are analysed using Item Response Theory (IRT). This theory describes the relationship between the ability of students taking a test and the difficulty of each item on that test. Using the assumption that a test item is a hard item if only the brightest students answer it correctly and that bright students are those students who can answer even the hardest items correctly, IRT is a generalized iterative procedure that can be used to simultaneously estimate both the difficulty of items on a test and the ability of those taking the test. This talk will give an overview of this technique and will demonstrate its use in measuring student ability. In particular the use of IRT models to construct Maths ability scores will be briefly discussed and how the results are communicated to teachers discussed.
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Pijáčková, Kristýna, Tomáš Gotthans, and Jakub Gotthans. "Model Ensembeling: A simple way of improving model performance for chromosome classification." In STUDENT EEICT 2022. Brno: Fakulta elektrotechniky a komunikacnich technologii VUT v Brne, 2022. http://dx.doi.org/10.13164/eeict.2022.158.
Li, Kin Fun, David Rusk, and Fred Song. "Predicting Student Academic Performance." In 2013 7th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS). IEEE, 2013. http://dx.doi.org/10.1109/cisis.2013.15.
Shaffer, Clifford A., and Stephen H. Edwards. "Scheduling and student performance." In the 16th annual joint conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1999747.1999842.
Chindhe, Tushar B., and Bhagya M. Patil. "Student Performance Appraisal System." In 2021 6th International Conference on Communication and Electronics Systems (ICCES). IEEE, 2021. http://dx.doi.org/10.1109/icces51350.2021.9489162.
Thai-Nghe, Nguyen, Tomas Horv´th, and Lars Schmidt-Thieme. "Personalized Forecasting Student Performance." In 2011 11th IEEE International Conference on Advanced Learning Technologies (ICALT). IEEE, 2011. http://dx.doi.org/10.1109/icalt.2011.130.
Malin, Helen. "Evaluating student employee performance." In the 34th annual ACM SIGUCCS conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1181216.1181264.
Abdullah, Nurul Ain, Mohd Khata Bin Jabor, Mohamad Alif Ismail, Ahmad Shobah Mohd Isa, and Hanim Zainal. "Social Media as a Means to Enhance Business Performance." In International Conference on Student and Disable Student Development 2019 (ICoSD 2019). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/assehr.k.200921.036.
Kenny Bagus, Ignasius, Luwita, Nasrullah, and Dina Fityria Murad. "Student Performance Based on Student Final Exam Prediction." In 2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI). IEEE, 2021. http://dx.doi.org/10.1109/iccsai53272.2021.9609716.
Eberts, Randall W., Kevin Hollenbeck, and Joe Allan Stone. Teacher Performance Incentives and Student Outcomes. W.E. Upjohn Institute, August 2000. http://dx.doi.org/10.17848/wp00-65.
Figlio, David, and Lawrence Kenny. Individual Teacher Incentives And Student Performance. Cambridge, MA: National Bureau of Economic Research, October 2006. http://dx.doi.org/10.3386/w12627.
Scott-Clayton, Judith, and Lauren Schudde. Performance Standards in Need-Based Student Aid. Cambridge, MA: National Bureau of Economic Research, October 2016. http://dx.doi.org/10.3386/w22713.
Thomson, Sue, Nicole Wernert, Sima Rodrigues, and Elizabeth O'Grady. TIMSS 2019 Australia. Volume I: Student performance. Australian Council for Educational Research, December 2020. http://dx.doi.org/10.37517/978-1-74286-614-7.
The Trends in International Mathematics and Science Study (TIMSS) is an international comparative study of student achievement directed by the International Association for the Evaluation of Educational Achievement (IEA). TIMSS was first conducted in 1995 and the assessment conducted in 2019 formed the seventh cycle, providing 24 years of trends in mathematics and science achievement at Year 4 and Year 8. In Australia, TIMSS is managed by the Australian Council for Educational Research (ACER) and is jointly funded by the Australian Government and the state and territory governments. The goal of TIMSS is to provide comparative information about educational achievement across countries in order to improve teaching and learning in mathematics and science. TIMSS is based on a research model that uses the curriculum, within context, as its foundation. TIMSS is designed, broadly, to align with the mathematics and science curricula used in the participating education systems and countries, and focuses on assessment at Year 4 and Year 8. TIMSS also provides important data about students’ contexts for learning mathematics and science based on questionnaires completed by students and their parents, teachers and school principals. This report presents the results for Australia as a whole, for the Australian states and territories and for the other participants in TIMSS 2019, so that Australia’s results can be viewed in an international context, and student performance can be monitored over time. The results from TIMSS, as one of the assessments in the National Assessment Program, allow for nationally comparable reports of student outcomes against the Melbourne Declaration on Educational Goals for Young Australians. (Ministerial Council on Education, Employment, Training and Youth Affairs, 2008).
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Figlio, David, and Maurice Lucas. Do High Grading Standards Affect Student Performance? Cambridge, MA: National Bureau of Economic Research, October 2000. http://dx.doi.org/10.3386/w7985.
Hanushek, Eric, and Margaret Raymond. Does School Accountability Lead to Improved Student Performance? Cambridge, MA: National Bureau of Economic Research, June 2004. http://dx.doi.org/10.3386/w10591.
Grissom, Jason, Demetra Kalogrides, and Susanna Loeb. Using Student Test Scores to Measure Principal Performance. Cambridge, MA: National Bureau of Economic Research, November 2012. http://dx.doi.org/10.3386/w18568.
Austin, Wes, Garth Heutel, and Daniel Kreisman. School Bus Emissions, Student Health, and Academic Performance. Cambridge, MA: National Bureau of Economic Research, March 2019. http://dx.doi.org/10.3386/w25641.
Gilraine, Michael, and Angela Zheng. Air Pollution and Student Performance in the U.S. Cambridge, MA: National Bureau of Economic Research, May 2022. http://dx.doi.org/10.3386/w30061.
Ward, Justin. Gentrification and Student Achievement: A Quantitative Analysis of Student Performance on Standardized Tests in Portland's Gentrifying Neighborhoods. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.6743.
