scholarly journals Academic performance of secondary education students in socio-familial risk contexts

2021 ◽  
Vol 28 (2) ◽  
Author(s):  
Daniel Rodríguez-Rodríguez ◽  
◽  
Remedios Guzmán ◽  
Keyword(s):  
At Risk ◽  
Academic Performance ◽  
Secondary Education ◽  
Self Efficacy ◽  
At Risk Students ◽  
Familial Risk ◽  
Course Evaluation ◽  
Self Concept ◽  
Cognitive Variables ◽  
Not At Risk

Introduction: The relationship that socio-familial and non-cognitive variables have on students in regards to their academic performance is a very important element for success in Secondary Education. In this study the influence of non-cognitive variables (academic self-concept, self-efficacy and perceived family affective support) and socio-familial variables (educational level and expectations of each parent) on the academic performance of secondary school students were analysed. Method: Students were grouped according to their accumulated socio-familial risk index (at-risk students, n = 305; not-at-risk students, n = 991). To measure the variables, the scales What do you think of yourself, General Self-Efficacy and Perceived Family Support were used. Socio-family variables were measured with an ad hoc questionnaire, and academic performance with the end-of-course evaluation scores. Results: The receiver operating characteristic curve showed a decrease in students’ academic performance from three or more accumulated risks. Structural Equation Modelling (SEM) was performed for each group. The results showed that for at-risk students, academic performance was mainly determined by two variables: academic self-concept and self-concept; in contrast to the not-at-risk students in which self-efficacy was the one that had the greatest effect on performance. In both groups, the parents’ expectations were the family variable with the highest incidence being performance, although, for the at-risk group, the effect was greater. Conclusions: The relevance of the identification of non-cognitive and socio-familial variables on the academic performance of at-risk students in regards to secondary education due to socio-familial factors is discussed.

scholarly journals Early Detection of At-Risk Undergraduate Students through Academic Performance Predictors

2017 ◽  
Vol 7 (3) ◽  
pp. 42
Author(s):  
Vikash Rowtho
Keyword(s):  
At Risk ◽  
Academic Performance ◽  
Early Detection ◽  
Undergraduate Students ◽  
At Risk Students ◽  
Regression Analyses ◽  
Linear Discriminant ◽  
Student Dropout ◽  
Performance Predictors ◽  
A New Technique

Undergraduate student dropout is gradually becoming a global problem and the 39 Small Islands Developing States (SIDS) are no exception to this trend. The purpose of this research was to develop a method that can be used for early detection of students who are at-risk of performing poorly in their undergraduate studies. A sample of 279 students participated in the study conducted in a Mauritian private tertiary academic institution. Results of regression analyses identified the variables having a significant influence on academic performance. These variables were used in a linear discriminant analysis where 74 percent of the students could be correctly classified into three categories: at-risk, pass or fail. In conclusion, this study has proposed a new technique that can be used by institutions to determine significant academic performance predictors and then identify at-risk students upon whom interventions can be implemented prior to exams to address the problem of dropouts.

scholarly journals Effectiveness of Tutoring to Improve Academic Performance in Nursing Students at the University of Seville

2017 ◽  
Vol 6 (2) ◽  
pp. 93-102 ◽  
Author(s):  
María Dolores Guerra-Martín ◽  
Marta Lima-Serrano ◽  
Joaquín Salvador Lima-Rodríguez
Keyword(s):  
At Risk ◽  
Academic Performance ◽  
Nursing Students ◽  
At Risk Students ◽  
Intervention Group ◽  
Academic Failure ◽  
Program Satisfaction ◽  
Tutoring Program ◽  
Information Comprehension ◽  
Education Support

In response to the increase of Higher Education support provided to tutoring programs, this paper presents the design, implementation and evaluation of a tutoring program to improve the academic performance of at-risk students enrolled in the last year of a nursing degree characterized by academic failure (failed courses). A controlled experimental study was carried out to evaluate a tutoring program that included a minimum of nine meetings performed by an expert professor as tutor. A questionnaire for assessing the academic needs was designed and interventions were performed when responses were: nothing, a little or something. Medium to large effects were found in the progress of failed course to passed course (p =.000, rφ = .30), improving the information about courses (p < .001, d = 2.01), the information comprehension (p < .001, d = 0.85) and the strategies to improve academic performance (p < .001, d = 1.37). The intervention group students’ response highlighted program satisfaction and effectiveness. The significance of the study lies in reinforcing the formal tutoring as a tool to improve academic performance in at-risk students.

Self-Concept Correlates between At-Risk and Not-At-Risk Ninth-Grade Students

1995 ◽  
Vol 76 (2) ◽  
pp. 683-687 ◽  
Author(s):  
Mary H. Jackson ◽  
Kimberly B. Reddick ◽  
Richard G. Dubes
Keyword(s):  
At Risk ◽  
Ninth Grade ◽  
Self Concept ◽  
Dropping Out ◽  
Satisfaction Scale ◽  
Ninth Grade Students ◽  
Not At Risk ◽  
Multivariate Discriminant ◽  
Item Scale

This study examined whether the Tennessee Self-concept Scales could be used to discriminate among 43 ninth-grade students who were designated as being at risk of dropping out of high school and 47 students who were thought to show probability of persisting. Scores on the scales were submitted to stepwise multivariate discriminant analysis. Scores on the Self-satisfaction Scale constituted a linear function that correctly classified 72.22% of the subjects. Further investigation confirmed a 13-item scale selected from the Tennessee Self-concept Scales correctly identified the classification of 76.67% of the students.

scholarly journals Goal Setting and Self-Efficacy Among Delinquent, At-Risk and Not At-Risk Adolescents

2012 ◽  
Vol 42 (3) ◽  
pp. 431-443 ◽  
Author(s):  
Annemaree Carroll ◽  
Kellie Gordon ◽  
Michele Haynes ◽  
Stephen Houghton
Keyword(s):  
At Risk ◽  
Goal Setting ◽  
Self Efficacy ◽  
Not At Risk ◽  
At Risk Adolescents

scholarly journals Using Heart Rate to Predict Students’ Academic Performance

2019 ◽  
Vol 8 (3) ◽  
pp. 5916-5920
Keyword(s):  
At Risk ◽  
Heart Rate ◽  
Academic Performance ◽  
Prediction Models ◽  
At Risk Students ◽  
Rate Data ◽  
Threshold Values ◽  
Heart Rate Data ◽  
Rate Fluctuation ◽  
Remedial Intervention

Timeliness was a missing factor in many studies on Academic Performance Prediction to identify at-risk students. This study embarked on a search to evaluate the feasibility of predicting students’ performance based on heart rate data collected during classes. This dimension of data was collected in the first four weeks after semester commencement to validate accurate prediction that will enable educationists to introduce remedial intervention to at-risk students. Another aim of this study is to determine the best threshold values for the different types of heart rate fluctuations that can be used in predicting academic achievements. The threshold values were tested further to verify whether the prediction model for individual course or combined courses was more accurate. Results revealed that heart rate data alone can achieve a maximum prediction accuracy of 88% and recall of 100%. Threshold values calculated in derived heart rate fluctuation types produces the best results. Prediction models for individual courses outperform the model using average threshold values of all courses.

scholarly journals Freshman Engineering Students At-Risk Of Non-Matriculation: Self-Efficacy For Academic Learning

2016 ◽  
Vol 7 (1) ◽  
pp. 9-18 ◽  
Author(s):  
Jeremy Ernst ◽  
Bradley D. Bowen ◽  
Thomas O. Williams
Keyword(s):  
At Risk ◽  
Self Efficacy ◽  
Engineering Students ◽  
Risk Indicators ◽  
Academic Learning ◽  
First Year ◽  
Grade Point ◽  
Cumulative Grade Point Average ◽  
Item Level ◽  
Not At Risk

Students identified as at-risk of non-academic continuation have a propensity toward lower academic self-efficacy than their peers (Lent, 2005). Within engineering, self-efficacy and confidence are major markers of university continuation and success (Lourens, 2014 Raelin, et al., 2014).  This study explored academic learning self-efficacy specific to first-year engineering students with at-risk indicators.  The at-risk determination was made through trajectory to matriculate, classified by cumulative grade point average of academic studies. An adapted version of the Self-efficacy for Learning (SEL) scale, modified by Klobas, Renzi and Nigrelli (2007), was administered to freshman engineering students identified at-risk and not at-risk of matriculation. Internal consistency of the SEL was analyzed and once deemed satisfactory (Cronbach alpha = .94), item-level outcome comparisons between student subgroups were made for each of the 22 instrument items.

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