scholarly journals Work in Progress: First-year Engineering Students’ Study Strategies and Their Academic Performance

2020 ◽  
Author(s):  
Ahmed Ashraf Butt ◽  
Saira Anwar ◽  
Muhsin Menekse
1994 ◽  
Vol 75 (3) ◽  
pp. 1219-1226 ◽  
Author(s):  
Wim Chr. Kleijn ◽  
Henk M. van der Ploeg ◽  
Robert M. Topman

The Study Management and Academic Results Test (SMART) was developed to measure study- and examination-related cognitions, time management, and study strategies. This questionnaire was used in three prospective studies, together with measures for optimism and test anxiety. In the first two studies, done among 253 first-year students enrolled in four different faculties, the highest significant correlations with academic performance were found for the SMART scales. In a replication study among first-year medical students ( n = 156) at a different university, the same pattern of results was observed. A stepwise multiple regression analysis, with academic performance as a dependent variable, showed significant correlations only for the SMART Test Competence and Time Management (Multiple R = .61). Results give specific indications about the profile of successful students.


Author(s):  
Boris Taratutin ◽  
Taylor Lobe ◽  
Jonathan Stolk ◽  
Robert Martello ◽  
Katherine C. Chen ◽  
...  

2005 ◽  
Vol 5 (1) ◽  
pp. 25-46 ◽  
Author(s):  
Mervyn Skuy ◽  
Melissa Skuy

In previous studies significant differences in measured intelligence between African and non-African first year engineering students have been found. Intellectual ability was found to correlate with academic performance, and black studednts had higher dropout and failure rates and performed less well than did their non-African counterparts. Given the low magnitude (r = 0.3), albeit significant, of the correlation between intelligence and academic performance, the question arose of the role of non-intellective factors, relative to intelligence, in determining academic performance of engineering students at University. Accordingly, 93% (n=100) of the second year Chemical and Metallurgical Engineering class were assessed on two measures of intellectual ability, and on measures of self concept, motivation, study attitudes and strategies, anxiety, locus of control, and autonomy. Whereas the intelligence test scores of non-African students (n=36) were significantly higher than those of African students (n=64), this was not the case for any of the non-intellective measures, or for academic achievement. Moreover, although the intellectual measures did not yield significant correlations with academic achievement, certain of the non-intellective measures did, and were able to differentiate between high and low academic performers. This was particularly true for the African group, suggesting that non-intellective variables can contribute significantly to academic performance, particularly in mitigating the effects of lower IQ.


2018 ◽  
Author(s):  
Mohammad Zahid ◽  
Evin Groundwater ◽  
Yanfen Li ◽  
Celia Elliott ◽  
Andrew Smith ◽  
...  

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