Collaborative Learning for Outcome Based Engineering Education: A Lean Thinking Approach

Bhat, Shreeranga; Bhat, Sathyendra; Raju, Ragesh; D’Souza, Rio; Binu, K G

doi:10.1016/j.procs.2020.05.134

Cited by 29 publications

(18 citation statements)

References 13 publications

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“…The EC-DT algorithm is selected to analyze the assessment management module in the HRM system. The selected indicators include team spirit (TS), sense of responsibility (R), creation spirit (CS), working ability (WA), morality and deeds (MD), communication and coordination (CC), and cost awareness (CA) [ 25 ]. The classification effect is evaluated by scoring results.…”

Section: Methodsmentioning

confidence: 99%

Influence of data mining technology in information analysis of human resource management on macroscopic economic management

Ai¹

2021

PLoS ONE

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The purposes are to manage human resource data better and explore the association between Human Resource Management (HRM), data mining, and economic management. An Ensemble Classifier-Decision Tree (EC-DT) algorithm is proposed based on the single decision tree algorithm to analyze HRM data. The involved single decision tree algorithms include C4.5, Random Tree, J48, and SimpleCart. Then, an HRM system is established based on the designed algorithm, and the evaluation management and talent recommendation modules are tested. Finally, the designed algorithm is compared and tested. Experimental results suggest that C4.5 provides the highest classification accuracy among the single decision tree algorithms, reaching 76.69%; in contrast, the designed EC-DT algorithm can provide a classification accuracy of 79.97%. The proposed EC-DT algorithm is compared with the Content-based Recommendation Method (CRM) and the Collaborative Filtering Recommendation Method (CFRM), revealing that its Data Mining Recommendation Method (DMRM) can provide the highest accuracy and recall, reaching 35.2% and 41.6%, respectively. Therefore, the data mining-based HRM system can promote and guide enterprises to develop according to quantitative evaluation results. The above results can provide a reference for studying HRM systems based on data mining technology.

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Section: Methodsmentioning

confidence: 99%

Influence of data mining technology in information analysis of human resource management on macroscopic economic management

Ai¹

2021

PLoS ONE

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“…To summarize, the transfer of Lean thinking from the manufacturing sector to the education sector, in particular to HEIs, has profound effects on the productivity and engagement of students, as well as the efficiency of teaching methodologies and techniques. Lean thinking creates an educational environment that aims for continuous improvement, through the reduction of non-value-added wastes and collaborative, heterogenous learning, as implied by Bhat et al [16]. However, the successful introduction of Lean thinking methodologies into HEIs is only effective when the entire organization adopts the idea, as efficient channels of communication are required between departments.…”

Section: Literature Reviewmentioning

confidence: 99%

The Effect of Teaching–Learning Environments on Student’s Engagement with Lean Mindset

Khandan

Shannon

2021

Education Sciences

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Lean thinking is a methodology employed initially by manufacturing organizations such as Toyota and New Balance that aims to increase customer value whilst also maintaining a low level of waste. The Lean thinking tools and techniques employed in the manufacturing sector can also be transferred to other sectors and significantly improve the service or product, such as public sector organizations or Higher Education Institutions (HEI). In the current education climate, due to the pandemic (SARS-CoV-2, COVID-19), the majority of HEIs have moved to an online or hybrid teaching and learning environment. This has developed the principle that Lean thinking can be deployed in educational methods and techniques to greatly increase the level of student engagement and the efficiency of learning. The following study outlines the key waste sources found in three types of teaching–learning environments (face to face, online and hybrid) and provides practical implications to counter the non-value-added issues. The data for this study were gathered through a questionnaire from final year undergraduate engineering students. The results indicate that online teaching had the greatest effect on student engagement, based on the identification and weighted values of non-value-added issues. The study highlights the key Lean wastes within online, hybrid and face to face teaching, and provides key examples within the stated Lean waste to provide solutions to improve student engagement.

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“…Prinsip ini merupakan tindakan dasar bagi seseorang yang ingin menambah wawasan atau pengetahuan. Di jenjang perguruan tinggi, tingkat berpikir mahasiswa dalam belajar diharapkan pada standar yang kompleks yaitu level empat hingga level enam (Bhat et al, 2020;Surya & Syahputra, 2017;Zubaidah et al, 2017). Pada level yang lebih tingga, standar manajemen informasi di kalangan mahasiswa masih berkategori tinggi.…”

Section: Manajemen Informasiunclassified

Manajemen Informasi sebagai Penguatan Pemahaman Belajar di Era Pandemi Covid 19

Zulhafizh

2022

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Penelitian ini bertujuan untuk mendeskripsikan manajemen informasi yang dilakukan mahasiswa untuk penguatan pemahaman mereka saat belajar di masa pandemi covid 19. Metode penelitian dengan pendekatan kuantitatif. Sampel penelitian 169 mahasiswa Program Studi Pendidikan Bahasa dan Sastra Indonesi FKIP Universitas Riau. Teknik pengumpulan data berupa angket berskala Likert. Analisis data dengan cara mengamati setiap butir-butir angket melalui statistik deskriptif, analisis faktor, analisis korelasi, analisis uji t satu sampel. Hasil analisis menunjukkan data demografi rata-rata berkategori tinggi, yaitu 3,89645, kemudian upaya mengumpulkan informasi 4,08; melengkapi dan menambah informasi 4,27; menginterpretasi dan mensentesis informasi 3,72; mengevaluasi informasi 3,66; mengidentifikasi dan memetakan manfaat informasi 3,58. Dilihat dari analisis faktor, semua komponen dapat menjadi penentu dalam manajemen informasi untuk penguatan pemahaman belajar dengan nilai > 0,50. Pada analisis korelasi dan uji t satu sampel bahwa seluruh data berkorelasi dan diyakini memiliki peran yang signifikansi yang ditandai dengan 0,000 < 0,05. Upaya manajemen informasi di masa pandemi covid 19 dapat menjadi penguat pemahaman mahasiswa dalam belajar

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Collaborative Learning for Outcome Based Engineering Education: A Lean Thinking Approach

Cited by 29 publications

References 13 publications

Influence of data mining technology in information analysis of human resource management on macroscopic economic management

Influence of data mining technology in information analysis of human resource management on macroscopic economic management

The Effect of Teaching–Learning Environments on Student’s Engagement with Lean Mindset

Manajemen Informasi sebagai Penguatan Pemahaman Belajar di Era Pandemi Covid 19

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