Is college students’ trajectory associated with academic performance?

Lim, Hyoungjoon; Kim, Soohyun; Chung, Kyongmee; Lee, Kangjae; Kim, Taewhan; Heo, Joon

doi:10.1016/j.compedu.2021.104397

Cited by 14 publications

(8 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This tendency may have influenced the discussion activity's success. Self-study (vs. simply listening to lectures) enhanced discussions' effectiveness; indeed, when self-study precedes conversation, learning is more robust and academic outcomes are better [49].…”

Section: Discussionmentioning

confidence: 97%

Harnessing E-Portfolio Creation for Exam Success, Student Engagement, and Satisfaction

Lin

2023

2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)

View full text Add to dashboard Cite

Incorporating e-portfolio creation into the educational process can result in substantial gains for students. Yet the literature has presented limited empirical evidence on how to implement e-portfolio creation in classrooms. In this mixed-methods study conducted at a public Japanese university, the performance and participation of 17 students in an online Moodle course where e-portfolio creation was the central learning activity were observed and evaluated. The course adopted a new instructional design model (the CLEAR model) that promotes a constructivist, creation-based learning approach. Students were required to create their own eportfolio using Mahara, discuss peers' e-portfolios, and post written self-reflections on Moodle forums. As a pre-test-posttest intervention, the course significantly increased students' exam scores on the same test, engaged them intensively online and offline without instructor supervision, and was rated as a positive and satisfying learning experience by participants. Practical implications, limitations, and future research directions are discussed in closing.

show abstract

Section: Discussionmentioning

confidence: 97%

Harnessing E-Portfolio Creation for Exam Success, Student Engagement, and Satisfaction

Lin

2023

2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)

View full text Add to dashboard Cite

show abstract

“…Additionally, a different study developed an algorithm to improve students' academic performance by identifying those who had late homework. The researcher obtained the data by grouping the students in a mixed-educational course and using an internet scholar course [41].…”

Section: Data Mining Methodsmentioning

confidence: 99%

Development and Testing of Performance Scale Application as an Effective Electronic Tool to Enhance Students’ Academic Achievements

et al. 2022

View full text Add to dashboard Cite

Performance scale application (PSA) usage in the classroom is underutilized, despite the rapid progress of mobile phone and e-learning technology. Lack of self-learning, evaluation, satisfaction, and inability to choose appropriate specialties influence students’ academic achievement in secondary school. The objective of this study is to investigate the development and testing of PSA on students’ learning achievement in secondary school. The PSA was developed on the Android mobile operating system using the extra trees regression algorithm to predict student achievement in secondary school. Students in the 11th grade basic specialty were considered. Three specialties were used, namely scientific, literary, and industry. The variables examined include improving evaluation (IME), improving communication (IMC), improving scientific (IMSC), and satisfaction of learning (SOL). The findings demonstrated that the PSA accurately predicted the students’ choice of specialty, IMC, IMSC, SOL, personalized learning (L), distance L, mobile L, self L, and specialty L. The findings also indicated a positive and significant effect of the PSA on students’ learning achievement. This validates that the extra trees regression is an effective tool for the development of PSA. In conclusion, the PSA has efficiently predicted the choice of specialties and academic achievements of students in secondary schools.

show abstract

“…Students' semantic trajectory is tested by dynamic time distortion, hierarchical clustering, and variance analysis. The experimental results show that semantic trajectory is a relevant factor affecting student performance [39]. Silva et al analyze family characteristics, values, beliefs, expectations and family support, self-efficacy, goal progress, and academic achievement [40].…”

Section: Plos Onementioning

confidence: 99%

Multi-Layer Perception model with Elastic Grey Wolf Optimization to predict student achievement

2022

View full text Add to dashboard Cite

This study proposes a Grey Wolf Optimization (GWO) variant named Elastic Grey Wolf Optimization algorithm (EGWO) with shrinking, resilient surrounding, and weighted candidate mechanisms. Then, the proposed EGWO is used to optimize the weights and biases of Multi-Layer Perception (MLP), and the EGWO-MLP model for predicting student achievement is thus obtained. The training and verification of the EGWO-MLP prediction model are conducted based on the thirty attributes from the University of California (UCI) Machine Learning Repository dataset’s student performance dataset, including family features and personal characteristics. For the Mathematics (Mat.) subject achievement prediction, the EGWO-MLP model outperforms one model’s prediction accuracy, and the standard deviation possesses the stable ability to predict student achievement. And for the Portuguese (Por.) subject, the EGWO-MLP outperforms three models’ Mathematics (Mat.) subject achievement prediction through the training process and takes first place through the testing process. The results show that the EGWO-MLP model has made fewer test errors, indicating that EGWO can effectively feedback weights and biases due to the strong exploration and local stagnation avoidance. And the EGWO-MLP model is feasible for predicting student achievement. The study can provide reference for improving school teaching programs and enhancing teachers’ teaching quality and students’ learning effect.

show abstract

Is college students’ trajectory associated with academic performance?

Cited by 14 publications

References 41 publications

Harnessing E-Portfolio Creation for Exam Success, Student Engagement, and Satisfaction

Harnessing E-Portfolio Creation for Exam Success, Student Engagement, and Satisfaction

Development and Testing of Performance Scale Application as an Effective Electronic Tool to Enhance Students’ Academic Achievements

Multi-Layer Perception model with Elastic Grey Wolf Optimization to predict student achievement

Contact Info

Product

Resources

About