This article briefs about application of evidence-based learning analytics on performance enhancement of undergraduate students in proficiency skills as per current industrial employability needs.
Inhaltsverzeichnis (Table of Contents)
- ABSTRACT
- INTRODUCTION
- RESEARCH METHODOLOGY
- RESULTS AND DISCUSSIONS
- Conclusion
- Acknowledgment
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This article investigates the application of evidence-based learning analytics to enhance the performance of undergraduate engineering students in proficiency skills relevant to current industrial employability needs. The authors demonstrate the use of a cloud-based employability tool for skill improvement, analyzing the performance of students across various disciplines and proficiency tests.
- Application of learning analytics for skill enhancement
- Evaluation of undergraduate engineering student proficiency in employability skills
- Analysis of test performance data across different disciplines and skill areas
- Assessing the effectiveness of cloud-based employability tools
- Providing insights for improving learning environments and generating employability indicators
Zusammenfassung der Kapitel (Chapter Summaries)
- ABSTRACT: This section introduces the article's focus on evidence-based learning analytics and its application to enhance undergraduate engineering student performance in employability skills.
- INTRODUCTION: This section emphasizes the importance of proficiency levels assessment, continuous monitoring, and analysis of employability skills as indicators of educational quality. It introduces the concept of evidence-based learning analytics and its implementation through a cloud-based employability tool.
- RESEARCH METHODOLOGY: This section details the methodology employed in the research, including the sample size (4000 test results from various engineering disciplines), the test series structure (150 tests in Aptitude, Technical, and English proficiency over four years), and the analytical approach (using Tableau software to analyze test scores).
- RESULTS AND DISCUSSIONS: This section presents the findings of the study, focusing on the performance data of students across different disciplines, including their variations in test scores and the frequency of tests taken. It includes tables showcasing sample data and descriptive statistics of test performance.
Schlüsselwörter (Keywords)
This article focuses on key concepts and themes related to learning analytics, employability skills assessment, and cloud-based tools in the context of undergraduate engineering education. It emphasizes the importance of evidence-based learning analytics for improving student performance and generating indicators on employability skills, particularly in relation to the current industrial needs. The main keywords include learning analytics, employability skills, proficiency tests, evaluation, training, and cloud-based employability (CBE).
- Quote paper
- Venkata Aditya Nag Mannepalli (Author), Dr. Myneni Madhu Bala (Author), B. Padmaja (Author), 2018, Learning Analytics On Cloud Based Employability Skill Test Series. Data On Proficiency Tests Performance Of Undergraduate Engineering Students, Munich, GRIN Verlag, https://www.grin.com/document/436400
