An Intervention Program for Advancing the Academic Performance of International Pathway “STAR”

2018 ◽  
pp. 71-95
Author(s):  
Donna Marie Velliaris
Keyword(s):  
Academic Performance ◽  
Student Performance ◽  
Study Skills ◽  
Intervention Program ◽  
Independent Study ◽  
Evidence Based ◽  
Self Directed Learning ◽  
Students At Risk ◽  
Support Strategy ◽  
Directed Learning

As part of an intervention and support strategy, this chapter discusses the evidence-based merits of a tertiary skills development (TSD) course delivered at the Eynesbury Institute of Business and Technology (EIBT) to “students at risk” (STAR). The effectiveness of the TSD course was measured via quantitative means by comparing students' academic performance before, during, and after TSD intervention. It was found that student performance analysed over three consecutive trimesters underwent a significant improvement when the support strategy was provided, followed by a small downturn in performance when the support was removed and students were again relying solely on their independent study skills and self-directed learning.

scholarly journals Impact of intrapersonal and interpersonal emotional intelligence and self-directed learning on academic performance among pre-university science students

Heliyon ◽  
2021 ◽  
Vol 7 (3) ◽  
pp. e06611
Author(s):  
Emmanuel Nkemakolam Okwuduba ◽  
Kingsley Chinaza Nwosu ◽  
Ebele Chinelo Okigbo ◽  
Naomi Nkiru Samuel ◽  
Chinwe Achugbu
Keyword(s):  
Emotional Intelligence ◽  
Academic Performance ◽  
Science Students ◽  
Self Directed Learning ◽  
Directed Learning ◽  
University Science

scholarly journals Readiness for Self-directed Learning and Academic Performance in an Abilities Laboratory Course

2011 ◽  
Vol 75 (2) ◽  
pp. 25 ◽  
Author(s):  
Zachariah M. Deyo ◽  
Donna Huynh ◽  
Charmaine Rochester ◽  
Deborah A. Sturpe ◽  
Katie Kiser
Keyword(s):  
Academic Performance ◽  
Self Directed Learning ◽  
Laboratory Course ◽  
Directed Learning

scholarly journals Modeling E-Behaviour, Personality and Academic Performance with Machine Learning

2021 ◽  
Vol 11 (22) ◽  
pp. 10546
Author(s):  
Serepu Bill-William Seota ◽  
Richard Klein ◽  
Terence van Zyl
Keyword(s):  
Machine Learning ◽  
At Risk ◽  
Academic Performance ◽  
Student Performance ◽  
Correlation Coefficients ◽  
Students At Risk ◽  
Intervention Process ◽  
Population Correlation ◽  
Online Behaviour ◽  
Personality Features

The analysis of student performance involves data modelling that enables the formulation of hypotheses and insights about student behaviour and personality. We extract online behaviours as proxies to Extraversion and Conscientiousness, which have been proven to correlate with academic performance. The proxies of personalities we obtain yield significant (p<0.05) population correlation coefficients for traits against grade—0.846 for Extraversion and 0.319 for Conscientiousness. Furthermore, we demonstrate that a student’s e-behaviour and personality can be used with deep learning (LSTM) to predict and forecast whether a student is at risk of failing the year. Machine learning procedures followed in this report provide a methodology to timeously identify students who are likely to become at risk of poor academic performance. Using engineered online behaviour and personality features, we obtain a classification accuracy (κ) of students at risk of 0.51. Lastly, we show that we can design an intervention process using machine learning that supplements the existing performance analysis and intervention methods. The methodology presented in this article provides metrics that measure the factors that affect student performance and complement the existing performance evaluation and intervention systems in education.

scholarly journals Self-Directed Learning versus Problem-Based Learning in Korean Nurse Education: A Quasi-Experimental Study

Healthcare ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1763
Author(s):  
Jaehee Jeon ◽  
Sihyun Park
Keyword(s):  
Experimental Study ◽  
Academic Performance ◽  
Nursing Students ◽  
Problem Based Learning ◽  
Nurse Education ◽  
Learning Motivation ◽  
Learning Ability ◽  
Self Directed Learning ◽  
Quasi Experimental ◽  
Directed Learning

Effective teaching methods are vital for cultivating advanced professional skills in nurses and equipping them with the necessary training. Problem-based learning (PBL) and self-directed learning (SDL) have been consistently used in nurse education. Therefore, their effects on nursing students’ academic performance warrant comparison. This study compared the effects of PBL and SDL on an adult nursing university curriculum. Participants in this quasi-experimental study with a pre-post non-equivalent control group design were 106 third-year nursing students divided into the PBL and SDL groups. Data collection, conducted from April to June 2019, included a pre-test before an eight-week intervention, followed by a post-test. Changes in the scores of each group were analyzed for learning motivation, self-directed learning ability, self-efficacy, learning confidence, learning satisfaction, and academic performance using paired and independent t-tests. The PBL group scored higher on learning motivation, self-directed learning ability, and academic performance than the SDL group. Based on these results, the PBL method was more effective than the SDL method in an adult nursing curriculum. To maximize the learning effect in adult nursing education, it is necessary to apply SDL education, including the PBL method, with a clearer learning process.

Does culture or self-directed learning drive online performance?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qian Wang ◽  
Chang Xiong ◽  
Jiajun Liu
Keyword(s):  
College Students ◽  
Student Performance ◽  
Learning Experience ◽  
Cultural Orientation ◽  
Self Directed Learning ◽  
Scoring Method ◽  
Content Type ◽  
Team Members ◽  
Directed Learning ◽  
The Impact

PurposeThe foundations of internally driven discipline are similar to self-directed learning (SDL). This study examines the effect of cultural orientation and SDL on the online performance of college students. It investigates how college students pursue SDL while maintaining a collectivist cultural orientation in their learning experience. It explains why students prefer SDL to learning constrained by an externally enforced discipline.Design/methodology/approachThe explanatory sequential mixed-method design uses a quantitative method, followed by qualitative enquiry. The research was conducted in an undergraduate non-credit online course in China.FindingsThe findings show that cultural orientation has no impact on students' online performance, while SDL abilities are positively related to it. When fully mediated by SDL, a horizontal-collectivist culture has a positive effect on students' online performance.Research limitations/implicationsData were collected in a non-credit online college course, where the final assessment used a peer-rating approach and team members shared the same final score. This scoring method may not fully reflect each student's online performance.Practical implicationsThe findings suggest that, when considering cultural influence on student performance, researchers should consider learning contexts, including educational level and learning mode. This study validates that colleges should focus on ability and skill development that enhance internal motivation to improve students' online performance, rather than focussing on their beliefs.Originality/valueThis paper introduces evidence to support the impact of culture on college students' online performance, showing that SDL abilities can drive performance.

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