scholarly journals Breadth of knowledge vs. grades: What best predicts achievement in the first year of health sciences programmes?

2012 ◽  
Vol 9 ◽  
pp. 7 ◽  
Author(s):  
Boaz Shulruf ◽  
Meisong Li ◽  
Judy McKimm ◽  
Melinda Smith
Keyword(s):  
Secondary School ◽  
Student Success ◽  
Grade Point Average ◽  
Grade Level ◽  
Health Sciences ◽  
Demographic Variables ◽  
First Year ◽  
Grade Point ◽  
The Impact ◽  
School Curricula

This study aimed to identify those features within secondary school curricula and assessment, particularly science subjects that best predict academic achievement in the first year of three different three-year undergraduate health professional programmes (nursing, pharmacy, and health sciences) at a large New Zealand university. In particular, this study compared the contribution of breadth of knowledge (number of credits acquired) versus grade level (grade point average) and explored the impact of demographic variables on achievement. The findings indicated that grades are the most important factor predicting student success in the first year of university. Although taking biology and physics at secondary school has some impact on university first year achievement, the effect is relatively minor.

scholarly journals First semester academic performance: The importance of early indicators of non-engagement

2018 ◽  
Vol 9 (4) ◽  
pp. 1-12 ◽  
Author(s):  
Jacques Van der Meer ◽  
Stephen Scott ◽  
Keryn Pratt
Keyword(s):  
Academic Performance ◽  
Student Success ◽  
Grade Point Average ◽  
First Year ◽  
First Year Students ◽  
Grade Point ◽  
Retention Strategy ◽  
First Semester ◽  
Efficiency And Effectiveness ◽  
The University

Success, progression and retention of students are goals of many university strategic directions and policies. For many decades it has been recognised that the greatest focus in any retention strategy should be on first-year students. University of Otago too has goals around student success. The Strategic Plan of the institution also identified that in the context of a fiscally constrained environment, all of our activities and processes need to be assessed for efficiency and effectiveness.  To this end, a pilot was undertaken in one area of the university to identify possible indicators of first-year students’ non-engagement in the first semester and their possible impact on the first semester academic performance. The findings suggest that there are indeed some indicators that predict Grade Point Average at the end of the first semester.

Impact of academic libraries on grade point average (GPA): a review

2020 ◽  
Vol 22 (1) ◽  
pp. 71-85
Author(s):  
Elizabeth A. Sterner
Keyword(s):  
Student Success ◽  
Grade Point Average ◽  
Academic Libraries ◽  
Relevant Literature ◽  
Academic Librarians ◽  
Academic Impact ◽  
Grade Point ◽  
Content Type ◽  
Student Privacy ◽  
The Impact

PurposeThe purpose of this paper is to examine the literature to determine how academic librarians are measuring their libraries' institutional level impact on student success as measured by grade point average, a metric commonly used in American education. This paper highlights a range of methods, outcomes and challenges in an initial scoping study.Design/methodology/approachThe methodology centered on a literature review of measuring the impact of academic libraries on student success as quantified by grade point average (GPA) from 2010 to present. Searches in ProQuest, EBSCO and Google Scholar were used to identify the relevant literature. Keywords searched in databases included various combinations of academic impact, student success, learning outcomes, library and higher education.FindingsThe analysis of 15 papers shows that academic librarians have demonstrated a small, nonnegligible positive correlation of library usage on GPA. The results of studies have highlighted that correlation does not prove the cause. Concerns and limitations of studies included using the GPA as a measurement of student success, differences between GPAs in subject areas, timeframes used, sample size collected, student privacy and the meanings of the results.Research limitations/implicationsThis study is limited to articles published in English measuring student success as quantified by GPA and focuses heavily on American sources.Originality/valueThe research can guide librarians through known challenges and highlight successful designs and study methods used by other academic librarians to measure the impact of the library on student success.

scholarly journals Developing Faculty Communities of Practice to Expand the Use of Effective Pedagogical Techniques

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Mark Hoyert ◽  
Cynthia O'Dell
Keyword(s):  
Student Success ◽  
Communities Of Practice ◽  
Teaching And Learning ◽  
Faculty Members ◽  
Retention Rates ◽  
First Year ◽  
Scholarship Of Teaching ◽  
Pedagogical Techniques ◽  
The Impact ◽  
Faculty Group

The scholarship of teaching and learning literature is replete with examples of pedagogical techniques that have been demonstrated to be effective in improving learning, motivation, and student success. The extension of these techniques beyond the original context has tended to be slow, difficult, and incomplete. The following paper examines an intervention designed to encourage the exploration and use of a variety of pedagogical techniques by faculty in a traditional, four-year college faculty within the context of the AASCU Re-imagining the First Year Initiative. Small groups of six to eight faculty, joined and created communities of practice. The groups were known as Pedagogical Interest Groups, or PIGs for short. The faculty read about and analyzed a series of pedagogical techniques and committed to introducing at least one technique into their courses to further explore the techniques. When the techniques were successful, the faculty members redesigned entire classes to expand the impact. The communities of practice were successful in encouraging faculty to explore a wide variety of techniques. The average faculty group explored eight different pedagogical techniques. Faculty were able to use the opportunity to experiment with techniques with the support from their colleagues in their PIG. A dozen techniques were explored across the PIGs and dozens of class sections have been completely redesigned. To date, over 2000 students have experienced redesigned courses. Measures of student success, satisfaction, and interest in those sections have increased. The effort has been accompanied by a robust increase in the campus-wide retention rates. ​

scholarly journals Impact of paid work on the academic performance of nursing students

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1838 ◽  
Author(s):  
Mery Constanza García-Vargas ◽  
Mercedes Rizo-Baeza ◽  
Ernesto Cortés-Castell
Keyword(s):  
Academic Performance ◽  
Nursing Students ◽  
Grade Point Average ◽  
Negative Impact ◽  
Paid Work ◽  
Cross Sectional ◽  
Work Activity ◽  
Grade Point ◽  
Increased Risk ◽  
The Impact

Background.Little research exists on the impact of paid work on academic performance of students of health sciences. No research exists on this subject for students in Colombia.Objectives.This paper seeks to analyze the impact of paid work on academic performance among nursing students. Design, settings and participants: cross-sectional research, involving 430 of nursing students from the National University of Colombia (N= 566).Methods.Variables analyzed: sex, age, work activity, attendance, current semester, degree subjects studied and unavailable, lost credits, grades during the second semester of 2013, and delayed semesters. Subgroups analyzed: (i) according to labor activity: do not work, work up to 20 h and work more than 20 h per week; (ii) Grade point average: failing is considered as less than 3.0 and passing 3.0 or above out of 5.0. Percentage of delayed semesters were calculated. Qualitative and quantitative variables were analyzed for groups by work activity. The percentage and probability of students getting a grade point average less than 3.0 and delaying semesters were calculated by multivariate logistic regression.Results. A total of 219 of the students work (50.9%), the main reason is socioeconomic, of which 99 (45.2%) work more than 20 h per week and have an increased risk of failing, which is higher in the first semester. They also get lower grades, lose more credits and take longer to finish the degree. The logistic bivariate regressions of success (grade point average, credits gained, courses gained and not having delayed semesters) reduce with work, above all in those who work more than 20 h per week and increase as the number of semesters completed increases, independent of sex.Conclusion.A high percentage of nursing students work more than 20 h per week. The compatibility of paid work with studies in university nursing students has a negative impact on academic performance, more so when they work more than 20 h per week. This negative impact diminishes as the student completes semesters, irrespective of the sex of the students.

scholarly journals Modeling of student academic achievement in engineering education using cognitive and non-cognitive factors

2019 ◽  
Vol 11 (2) ◽  
pp. 178-198 ◽  
Author(s):  
Bothaina A. Al-Sheeb ◽  
A.M. Hamouda ◽  
Galal M. Abdella
Keyword(s):  
Student Success ◽  
Student Performance ◽  
Success Factors ◽  
Comprehensive Approach ◽  
First Year ◽  
Valuable Insight ◽  
Data Set ◽  
Grade Point ◽  
Content Type ◽  
Second Year

Purpose The retention and success of engineering undergraduates are increasing concern for higher-education institutions. The study of success determinants are initial steps in any remedial initiative targeted to enhance student success and prevent any immature withdrawals. This study provides a comprehensive approach toward the prediction of student academic performance through the lens of the knowledge, attitudes and behavioral skills (KAB) model. The purpose of this paper is to aim to improve the modeling accuracy of students’ performance by introducing two methodologies based on variable selection and dimensionality reduction. Design/methodology/approach The performance of the proposed methodologies was evaluated using a real data set of ten critical-to-success factors on both attitude and skill-related behaviors of 320 first-year students. The study used two models. In the first model, exploratory factor analysis is used. The second model uses regression model selection. Ridge regression is used as a second step in each model. The efficiency of each model is discussed in the Results section of this paper. Findings The two methods were powerful in providing small mean-squared errors and hence, in improving the prediction of student performance. The results show that the quality of both methods is sensitive to the size of the reduced model and to the magnitude of the penalization parameter. Research limitations/implications First, the survey could have been conducted in two parts; students needed more time than expected to complete it. Second, if the study is to be carried out for second-year students, grades of general engineering courses can be included in the model for better estimation of students’ grade point averages. Third, the study only applies to first-year and second-year students because factors covered are those that are essential for students’ survival through the first few years of study. Practical implications The study proposes that vulnerable students could be identified as early as possible in the academic year. These students could be encouraged to engage more in their learning process. Carrying out such measurement at the beginning of the college year can provide professional and college administration with valuable insight on students perception of their own skills and attitudes toward engineering. Originality/value This study employs the KAB model as a comprehensive approach to the study of success predictors. The implementation of two new methodologies to improve the prediction accuracy of student success.

Success of Students Screened as Twice-Exceptional as a Function of Major Selection and Academic Strength

2020 ◽  
pp. 152102512091585
Author(s):  
Kelly H. Snyder ◽  
Virginia M. McClurg ◽  
Jiaju Wu ◽  
R. Steve McCallum
Keyword(s):  
Learning Disability ◽  
Grade Point Average ◽  
American College Test ◽  
Retention Rates ◽  
First Year ◽  
Twice Exceptional ◽  
Grade Point ◽  
Major Selection ◽  
Reverse Pattern ◽  
First Year Retention

In this study, the success of 6,054 college students screened as twice-exceptional (2e; i.e., those with significantly discrepant math vs. reading scores on the ACT [formerly, American College Test] or SAT [formerly, Scholastic Aptitude Test]) was examined based on major selection and type of potential learning disability using a screening technique proposed by McCallum et al. There were no differences in high school grade point average, college grade point average, or first-year retention rates between students screened as 2e who had a major in line with their academic strength versus those who did not ( p >  .05). However, students screened as 2e based on an exceptionally high math score but a lower reading score yielded statistically significantly higher rates of retention ( p <  .05) than students screened as 2e with the reverse pattern of scores (i.e., gifted in reading with a potential learning disability in math). Implications for screening 2e students are discussed.

The Validity of the GMAT for the Prediction of Grades in Doctoral Study in Business and Management: An Empirical Bayes Approach

1993 ◽  
Vol 18 (1) ◽  
pp. 91-107 ◽  
Author(s):  
Rebecca Zwick
Keyword(s):  
Grade Point Average ◽  
Doctoral Students ◽  
Empirical Bayes ◽  
Doctoral Programs ◽  
First Year ◽  
Mba Programs ◽  
Grade Point ◽  
Final Grade ◽  
Complex Models ◽  
Parsimonious Model

A validity study was conducted to examine the degree to which GMAT scores and undergraduate grade-point average (UGPA) could predict first-year average (FYA) and final grade-point average in doctoral programs in business. A variety of empirical Bayes regression models, some of which took into account possible differences in regressions across schools and cohorts, were investigated for this purpose. Indexes of model fit showed that the most parsimonious model, which did not allow for school or cohort effects, was just as useful for prediction as the more complex models. The three preadmissions measures were found to be associated with graduate school grades, though to a lesser degree than in MBA programs. The prediction achieved using UGPA alone as a predictor tended to be more accurate than that obtained using GMAT verbal (GMATV) and GMAT quantitative (GMATQ) scores together. Including all three predictors was more effective than using only UGPA. The most likely explanation for the lower levels of prediction than in MBA programs is that doctoral programs tend to be more selective. Within-school means on GMATV, GMATQ, UGPA, and FYA were higher than those found in MBA validity studies; within-school standard deviations on FYA tended to be smaller. Among these very select, academically competent doctoral students, highly accurate prediction of grades may not be possible.

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