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Journal articles on the topic 'Course performance'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Oducado, Ryan Michael F. "Are Nursing Students’ Early Course and Perceived Performance Related to Their Final and Actual Course Performance?" Nurse Media Journal of Nursing 9, no. 2 (2019): 167–75. http://dx.doi.org/10.14710/nmjn.v9i2.26675.

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Background: Assessing the academic performance of students is imperative for nursing educators. While it is commonly accepted that performance in quizzes is linked with final examination performance, little published empirical data is available among nursing student samples.Purpose: The purpose of this study was to determine the relationship between performance in regular short lecture quizzes and long quiz on the final examination performance of nursing students in a nursing course. Likewise, this study ascertained whether there is a significant relationship between perceived performance and

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2

Shub, C. M. "Performance experiments for the performance course." ACM SIGCSE Bulletin 21, no. 1 (1989): 222–25. http://dx.doi.org/10.1145/65294.71217.

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Lester, David. "Predicting Performance in a Psychological Statistics Course." Psychological Reports 101, no. 1 (2007): 334. http://dx.doi.org/10.2466/pr0.101.1.334-334.

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White, John. "A Course in Performance Art." Performing Arts Journal 17, no. 2/3 (1995): 133. http://dx.doi.org/10.2307/3245787.

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Pollock, Della. "Performance is a Collision Course." International Review of Qualitative Research 3, no. 2 (2010): 203–5. http://dx.doi.org/10.1525/irqr.2010.3.2.203.

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Dills, Angela K., and Rey Hernández-Julián. "Course scheduling and academic performance." Economics of Education Review 27, no. 6 (2008): 646–54. http://dx.doi.org/10.1016/j.econedurev.2007.08.001.

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Wesp, Richard, Kathleen Montgomery, and Charles Jacobson. "Students Tend to Overestimate Their Course Performance." Psychological Reports 79, no. 3 (1996): 864–66. http://dx.doi.org/10.2466/pr0.1996.79.3.864.

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Students in 84 courses estimated their grades as part of a confidential evaluation at the end of the course. Class average predictions were compared with average grades for those classes. A high portion of classes overestimate their actual performance.

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Lindsay Hall, Michael. "Linking Budgeting with Computational Thinking Pedagogy: Program Theory, Performance, and Budgeting." Frontiers of Contemporary Education 2, no. 2 (2021): p42. http://dx.doi.org/10.22158/fce.v2n2p42.

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The pedagogy involved with preparing and delivering an analytically based course must contend with a number of important limitations or challenges. The challenges/limitations include needing a context for the use of the analytics being taught; others include where best to embed analytic courses in degree curriculum, determining content and delivery along with a number of additional limitations. A context can be created for these courses by establishing a base of usefulness of the course content and how it relates to other courses and to professional applications. However, one useful approach f

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Siefken, Jason. "Registration Delay and Student Performance." Journal of the Scholarship of Teaching and Learning 17, no. 2 (2017): 45–52. http://dx.doi.org/10.14434/josotl.v17i2.20754.

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Tracking the difference between the time a first-year student is allowed to register for a course and the time he or she does register for a course (a student’s registration delay), we notice a negative correlation between registration delay and final grade in a course. The difference between a student who registers within the first two minutes they are allowed to and one who waits three weeks to register is approximately a full GPA point (on a 9 point scale). Registration delay may be a useful factor in helping to identify at-risk students, and should be taken into account as a confounding va

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Dvorak, Tomas, and Miaoqing Jia. "Online Work Habits and Academic Performance." Journal of Learning Analytics 3, no. 3 (2016): 318–30. http://dx.doi.org/10.18608/jla.2016.33.15.

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This study analyzes the relationship between students’ online work habits and academic performance. We utilize data from logs recorded by a course management system (CMS) in two courses at a small liberal arts college in the U.S. Both courses required the completion of a large number of online assignments. We measure three aspects of students’ online work habits: timeliness, regularity, and intensity. We find that students with a high overall GPA and a high grade in the course work on assignments early and more regularly. We also find that the regularity of work habits during the first half of

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Enderson, Mary C., and Manveer Mann. "Student Performance in Mathematics: Should we be Concerned?" International Journal of Adult Vocational Education and Technology 9, no. 1 (2018): 59–72. http://dx.doi.org/10.4018/ijavet.2018010105.

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This article describes how for many college students the transition to college-level mathematics courses presents new challenges beyond those that were part of the high school experience. In this interdisciplinary study forty-four non-mathematics and non-science majors, enrolled in a retail-buying course, were studied to examine student confidence in performing applied mathematical tasks, mathematics achievement in college, and the relationship between predictors of college success (mathematics studied in high school, SAT/ACT scores, and mathematics courses taken in college). Measurements used

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COUSINS-COOPER, KATHY, Dominic Clemence-MKHOPE, Katrina Nelson, Seongtae Kim, and Kelly McMurray. "ASSESSING THE EMPORIUM MODEL THROUGH STUDENT PERFORMANCE AND PERSISTENCE." International Journal for Innovation Education and Research 7, no. 7 (2019): 408–20. http://dx.doi.org/10.31686/ijier.vol7.iss7.1622.

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The mathematics emporium model (MEM) was implemented to improve student success and retention rates. The college algebra course sequence was redesigned using the emporium model to establish consistency, emphasize active learning, modularize course materials, and provide one-on-one personalized on-demand assistance from faculty and teaching assistants. The emporium model ensured consistent content coverage and learning experiences, improved course coherence, and improved quality control. This study compared the course performance of students enrolled in a college algebra and trigonometry course

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Titus, Weston, Richard Armenta, and Matthew Schubert. "Predictors of obstacle course racing performance." Human Movement 21, no. 2 (2020): 51–57. http://dx.doi.org/10.5114/hm.2020.89914.

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14

Yang, Bijou, and David Lester. "Working Students and Their Course Performance." Psychological Reports 62, no. 3 (1988): 826. http://dx.doi.org/10.2466/pr0.1988.62.3.826.

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Sankaran, Siva, and Kris Sankaran. "Improving Online Course Performance Through Customization." International Journal of Business Analytics 3, no. 4 (2016): 1–20. http://dx.doi.org/10.4018/ijban.2016100101.

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The number of educational courses offered online is growing, with students often having no choice for alternative formats. However, personal characteristics may affect online academic performance. In this study, the authors apply two business analytics methods - multiple linear/polynomial regression and generalized additive modeling (GAM) - to predict online student performance based on six personal characteristics. These characteristics are: communication aptitude, desire to learn, escapism, hours studied, gender, and English as a Second Language. Survey data from 168 students were partitione

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Freeman, Scott, David Haak, and Mary Pat Wenderoth. "Increased Course Structure Improves Performance in Introductory Biology." CBE—Life Sciences Education 10, no. 2 (2011): 175–86. http://dx.doi.org/10.1187/cbe.10-08-0105.

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We tested the hypothesis that highly structured course designs, which implement reading quizzes and/or extensive in-class active-learning activities and weekly practice exams, can lower failure rates in an introductory biology course for majors, compared with low-structure course designs that are based on lecturing and a few high-risk assessments. We controlled for 1) instructor effects by analyzing data from quarters when the same instructor taught the course, 2) exam equivalence with new assessments called the Weighted Bloom's Index and Predicted Exam Score, and 3) student equivalence using

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McCafferty, Renee, and Venkatareddy Nadithe. "Student Performance with Standalone Calculations Course vs Combined Pharmaceutics-Calculations Course." American Journal of Pharmaceutical Education 82, no. 7 (2018): 6312. http://dx.doi.org/10.5688/ajpe6312.

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Said, Hazem, Lauren Kirgis, Brian Verkamp, and Lawrence J Johnson. "Online vs. Face-to-Face Delivery of Information Technology Courses: Students' Assessment." Journal of Information Technology Education: Research 14 (2015): 297–312. http://dx.doi.org/10.28945/2274.

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This paper investigates students’ assessment of on-line vs face-to-face delivery of lecture-based information technology courses. The study used end-of-course surveys to examine students’ ratings of five course quality indicators: Course Organization, Assessment and Grading Procedures, Instructor Performance, Positive Learning Experience, and Perceived Success. The study analyzed five semesters of students’ ratings and found no significant differences in the overall ratings of the course quality indicators between the on-line and face-to-face courses. There were differences between the overall

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Jarchow, Meghann E., Paul Formisano, Shane Nordyke, and Matthew Sayre. "Measuring longitudinal student performance on student learning outcomes in sustainability education." International Journal of Sustainability in Higher Education 19, no. 3 (2018): 547–65. http://dx.doi.org/10.1108/ijshe-11-2016-0200.

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Purpose The purpose of this paper is to describe the student learning outcomes (SLOs) for a sustainability major, evaluate faculty incorporation of the SLOs into the courses in the sustainability major curriculum and measure student performance on the SLOs from entry into the major to the senior capstone course. Design/methodology/approach Through an iterative approach with a faculty advisory committee, SLOs were developed for the sustainability major. Curriculum mapping followed by evaluation of course syllabi were used to determine the extent to which each course addressed the SLOs. Student

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Chernov, Victor, Sivan Klas, and Yael Furman Shaharabani. "Incorporating Kahoot! in core engineering courses: Student engagement and performance." Journal of Technology and Science Education 11, no. 2 (2021): 486. http://dx.doi.org/10.3926/jotse.1269.

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Technology-enriched lessons can contribute to improving student engagement and learning in engineering courses. In this study we systematically incorporated Kahoot!, a game-based response system, in two mandatory content-intensive undergraduate engineering courses. In both courses, short quizzes were incorporated regularly at the beginning of the lesson. The questions were mostly about concepts, and students earned bonus points. At the end of the course, the students filled in an anonymous survey regarding their perceptions of the Kahoot! part of the lessons. In addition, the students’ grades

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Olusola, Ogunlade Bamidele, and Bello Lukuman Kolapo. "Pre-Service Teachers' Perceived Relevance of Educational Technology Course, Digital Performance." International Journal of Technology-Enabled Student Support Services 9, no. 1 (2019): 41–54. http://dx.doi.org/10.4018/ijtesss.2019010103.

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Educational technology courses are designed to equip prospective teachers with knowledge and skills to use technology for effective instructional delivery. However, the way students perceive the appropriateness and relevance of the instructional content would go a long way in determining their performance and commitment to the course. Student performance in educational technology courses could be improved, if they perceive the instructional content to be relevant to their academic pursuits and future career development. Therefore, this study examined pre-service teachers' perceived relevance o

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Garcia, Regina A., and Lilac A. Al-Safadi. "Intervention Strategies for the Improvement of Students’ Academic Performance in Data Structure Course." International Journal of Information and Education Technology 4, no. 5 (2014): 383–87. http://dx.doi.org/10.7763/ijiet.2014.v4.435.

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Creech, Leah Renée, and Ryan D. Sweeder. "Analysis of Student Performance in Large-Enrollment Life Science Courses." CBE—Life Sciences Education 11, no. 4 (2012): 386–91. http://dx.doi.org/10.1187/cbe.12-02-0019.

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This study examined the historical performance of students at Michigan State University in 12 life sciences courses over 13 yr to find variables impacting student success. Hierarchical linear modeling predicted 25.0–62.8% of the variance in students’ grades in the courses analyzed. The primary predictor of a student's course grade was his or her entering grade point average; except for the second course in a series (i.e., Biochemistry II), in which the grade for the first course in the series (i.e., Biochemistry I) was often the best predictor, as judged by β values. Student gender and major w

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24

Hughes, Thomas M., and Cordelia Douzenis. "Predictor and Performance Variables in a Performance-Based Education Course." Journal of Psychology 120, no. 2 (1986): 143–47. http://dx.doi.org/10.1080/00223980.1986.9712623.

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Yang, Jie, Shimin Hu, Qichao Wang, and Simon Fong. "Discriminable Multi-Label Attribute Selection for Pre-Course Student Performance Prediction." Entropy 23, no. 10 (2021): 1252. http://dx.doi.org/10.3390/e23101252.

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The university curriculum is a systematic and organic study complex with some immediate associated steps; the initial learning of each semester’s course is crucial, and significantly impacts the learning process of subsequent courses and further studies. However, the low teacher–student ratio makes it difficult for teachers to consistently follow up on the detail-oriented learning situation of individual students. The extant learning early warning system is committed to automatically detecting whether students have potential difficulties—or even the risk of failing, or non-pass reports—before

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Hart, Cassandra M. D., Dan Berger, Brian Jacob, Susanna Loeb, and Michael Hill. "Online Learning, Offline Outcomes: Online Course Taking and High School Student Performance." AERA Open 5, no. 1 (2019): 233285841983285. http://dx.doi.org/10.1177/2332858419832852.

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This article uses fixed effects models to estimate differences in contemporaneous and downstream academic outcomes for students who take courses virtually and face-to-face—both for initial attempts and for credit recovery. We find that while contemporaneous outcomes are positive for virtual students in both settings, downstream outcomes vary by attempt type. For first-time course takers, virtual course taking is associated with decreases in the likelihood of taking and passing follow-on courses and in graduation readiness (based on a proxy measure). For credit recovery students, virtual course

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27

Quintana, Rafael, and Christian Schunn. "Who Benefits From a Foundational Logic Course? Effects on Undergraduate Course Performance." Journal of Research on Educational Effectiveness 12, no. 2 (2019): 191–214. http://dx.doi.org/10.1080/19345747.2018.1543372.

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KRAWIEC, STEVEN, DIANE SALTER, and EDWIN J. KAY. "A “Hybrid” Bacteriology Course: The Professor’s Design and Expectations; The Students’ Performance and Assessment." Microbiology Education 6, no. 1 (2005): 8–13. http://dx.doi.org/10.1128/me.6.1.8-13.2005.

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A basic bacteriology course was offered in two successive academic years, first in a conventional format and subsequently as a “hybrid” course. The latter combined (i) online presentation of content, (ii) an emphasis on online resources, (iii) thrice-weekly, face-to-face conversations to advance understanding, and (iv) frequent student postings on an electronic discussion board. We compared the two courses through statistical analysis of student performances on the final examinations and the course overall and student assessment of teaching. The data indicated that there was no statistical dif

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Premalatha, M., and V. Viswanathan. "Course Sequence Recommendation with Course Difficulty Index Using Subset Sum Approximation Algorithms." Cybernetics and Information Technologies 19, no. 3 (2019): 25–44. http://dx.doi.org/10.2478/cait-2019-0024.

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Abstract Choice Based Course Selection (CBCS) allows students to select courses based on their preferred sequence. This preference in selection is normally bounded by constraints set by a university like pre-requisite(s), minimum and maximum number of credits registered per semester. Unplanned course sequence selection affects the performance of the students and may prolong the time to complete the degree. Course Difficulty Index (DI) also contributes to the decline in the performance of the students. To overcome these difficulties, we propose a new Subset Sum Approximation Problem (SSAP) aims

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30

Lake, D. A. "Peer tutoring improves student performance in an advanced physiology course." Advances in Physiology Education 276, no. 6 (1999): S86. http://dx.doi.org/10.1152/advances.1999.276.6.s86.

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Effectiveness of a peer tutoring system developed for an advanced physiology course was assessed in terms of academic performance and perceived value. Forty-five students took the course without the peer tutoring system, and sixty-nine students took the course with peer tutoring. Grades from both groups of students were compared with grades earned in an introductory physiology course. Tutored students were asked how much they valued the peer tutoring. There was a decline in grades received by the students in the advanced physiology course compared with their scores in the introductory physiolo

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Hubble, Michael W., and Michael E. Richards. "Paramedic Student Performance: Comparison of Online with On-Campus Lecture Delivery Methods." Prehospital and Disaster Medicine 21, no. 4 (2006): 261–67. http://dx.doi.org/10.1017/s1049023x00003800.

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AbstractIntroduction:Colleges and universities are experiencing increasing demand for online courses in many healthcare disciplines, including emergency medical services (EMS). Development and implementation of online paramedic courses with the quality of education experienced in the traditional classroom setting is essential in order to maintain the integrity of the educational process. Currently, there is conflicting evidence of whether a significant difference exists in student performance between online and traditional nursing and allied health courses. However, there are no published inve

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Cisero, Cheryl A. "Does Reflective Journal Writing Improve Course Performance?" College Teaching 54, no. 2 (2006): 231–36. http://dx.doi.org/10.3200/ctch.54.2.231-236.

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LESTER, DAVID. "PREDICTING PERFORMANCE IN A PSYCHOLOGICAL STATISTICS COURSE." Psychological Reports 101, no. 5 (2007): 334. http://dx.doi.org/10.2466/pr0.101.5.334-334.

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34

Lester, David. "Speed and Performance on College Course Examinations." Perceptual and Motor Skills 73, no. 3_suppl (1991): 1090. http://dx.doi.org/10.2466/pms.1991.73.3f.1090.

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Gopaldas, Pawan Kumar. "Variables Impacting Students� Performance in Management Course." SDMIMD Journal of Management 9, no. 2 (2018): 41–46. http://dx.doi.org/10.18311/sdmimd/2018/21472.

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SLEIVERT, GORDON G., and HOWARD A. WENGER. "Physiological predictors of short-course triathlon performance." Medicine & Science in Sports & Exercise 25, no. 7 (1993): 871–76. http://dx.doi.org/10.1249/00005768-199307000-00017.

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37

Gan Zhengdong. "IELTS Preparation Course and Student IELTS Performance." RELC Journal 40, no. 1 (2009): 23–41. http://dx.doi.org/10.1177/0033688208101449.

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Ha, Louisa, Fred Beard, and Roy Kelsey. "Students' Computer Skills and Advertising Course Performance." Journalism & Mass Communication Educator 53, no. 1 (1998): 33–43. http://dx.doi.org/10.1177/107769589805300105.

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&NA;. "Trauma Outcomes & Performance Improvement Course®." Journal of Trauma Nursing 11, no. 1 (2004): 46. http://dx.doi.org/10.1097/00043860-200411010-00008.

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&NA;. "Trauma Outcomes & Performance Improvement Course®." Neurosurgery Quarterly 11, no. 1 (2004): 46. http://dx.doi.org/10.1097/00013414-200411010-00008.

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Shub, Charles M. "A component part for a performance course." ACM SIGCSE Bulletin 18, no. 1 (1986): 120–23. http://dx.doi.org/10.1145/953055.5645.

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Bell, Kenneth E., and John E. Limber. "Reading Skill, Textbook Marking, and Course Performance." Literacy Research and Instruction 49, no. 1 (2009): 56–67. http://dx.doi.org/10.1080/19388070802695879.

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Titus, Weston, Richard F. Armenta, and Matthew M. Schubert. "Predictors Of Obstacle Course Racing (OCR) Performance." Medicine & Science in Sports & Exercise 52, no. 7S (2020): 1031. http://dx.doi.org/10.1249/01.mss.0000686808.67078.8d.

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Heines, Jesse M. "Evaluating course Web sites and student performance." ACM SIGCSE Bulletin 31, no. 3 (1999): 143–46. http://dx.doi.org/10.1145/384267.305898.

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Kelsch, Michael P., and Robert K. Sylvester. "The Effect of Prerequisite Pharmacodynamics Course Timing on Student Performance in Pharmacotherapy Courses." American Journal of Pharmaceutical Education 80, no. 6 (2016): 99. http://dx.doi.org/10.5688/ajpe80699.

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Chen, Jiaming, Liming Luo, and Jie Song. "Course performance prediction for basic courses of universities based on support vector machine." Journal of Physics: Conference Series 1168 (February 2019): 032066. http://dx.doi.org/10.1088/1742-6596/1168/3/032066.

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Serik, М., and G. Zh Yerlanova. "CONTENT OF A SPECIAL COURSE ON HIGH PERFORMANCE COMPUTING." BULLETIN Series of Physics & Mathematical Sciences 71, no. 3 (2020): 263–67. http://dx.doi.org/10.51889/2020-3.1728-7901.40.

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At present, along with the dynamic development of computer technology in the world, the most effective ways of solving problems of practical importance are being considered. High performance computing takes the lead in this. Therefore, the development of modern society is closely related to the training of experienced, modern specialists in the field of information technology. This, in turn, depends on the inclusion of new courses in the curriculum and full coverage of these issues in the content of the taught courses. This article analyzes the courses on high performance computing, taught at

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Cui, Ying, Fu Chen, and Ali Shiri. "Scale up predictive models for early detection of at-risk students: a feasibility study." Information and Learning Sciences 121, no. 3/4 (2020): 97–116. http://dx.doi.org/10.1108/ils-05-2019-0041.

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Purpose This study aims to investigate the feasibility of developing general predictive models for using the learning management system (LMS) data to predict student performances in various courses. The authors focused on examining three practical but important questions: are there a common set of student activity variables that predict student performance in different courses? Which machine-learning classifiers tend to perform consistently well across different courses? Can the authors develop a general model for use in multiple courses to predict student performance based on LMS data? Design

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Ferguson, Janet M., and Amy E. DeFelice. "Length of online course and student satisfaction, perceived learning, and academic performance." International Review of Research in Open and Distributed Learning 11, no. 2 (2010): 73. http://dx.doi.org/10.19173/irrodl.v11i2.772.

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This research presents findings from a two-part study. In the first part, graduate students taking online courses were given a course evaluation form. Student responses from online abbreviated summer sessions were compared to student responses from online full-semester courses.   Both the intensive and full-semester courses were taught by the same professor and both had identical requirements in terms of assignments and exams. The independent variable was the length of time taken to complete the requirements, with the dependent variables being satisfaction with the course, perceive

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Alstete, Jeffrey W., and Nicholas J. Beutell. "Business simulation and assurance of learning." Quality Assurance in Education 27, no. 4 (2019): 412–26. http://dx.doi.org/10.1108/qae-04-2018-0043.

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Purpose This study aims to consider assurance of learning among undergraduate business students enrolled in capstone business strategy courses using the GLO-BUS competitive simulation. Gender, academic major and business core course performance were examined. Design/methodology/approach Participants were 595 undergraduate capstone business students from 21 course sections taught over a four-year period. Variables included learning assurance measures, simulation performance, gender, major, business core course grades, capstone course grade and cumulative grade point average. Correlations, linea

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