CRADLE - Centre for Research and Development in Learning

The CRADLE (Centre for Research and Development in Learning) dataverse contains research data collected or generated by the Centre that specializes in empowering and transforming learners in higher education and lifelong learning and leading innovative interdisciplinary research founded on the Science of Learning.

For more information on CRADLE, visit Home page

Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

161 to 170 of 197 Results

Transcript 5.docx Jul 14, 2022 - Workplace learning in disruptive innovators: A knowledge management perspective MS Word - 33.3 KB - MD5: 04c555d8c50521e5b53b8023c5cb9637
Transcript 6.docx Jul 14, 2022 - Workplace learning in disruptive innovators: A knowledge management perspective MS Word - 27.3 KB - MD5: c91b9c713c86ebd5498f3c7104d05ce5
Transcript 7.docx Jul 14, 2022 - Workplace learning in disruptive innovators: A knowledge management perspective MS Word - 28.3 KB - MD5: 6dff3ae874e049ea7956f57ea972dda3
Transcript 8.docx Jul 14, 2022 - Workplace learning in disruptive innovators: A knowledge management perspective MS Word - 31.3 KB - MD5: a022a70d6ab5661eeff6939bb404559f
Transcript 9.docx Jul 14, 2022 - Workplace learning in disruptive innovators: A knowledge management perspective MS Word - 32.3 KB - MD5: b264fb1035349fa3c48ce517ff7518dd
Liuyu Huang(Nanyang Technological University) Jul 14, 2022 Appointment: Research Associate Research topics: • Workplace learning • Sharing economy • Data visualization • Bibliometrics
Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance Nov 16, 2021 Puah, Shermain; Bin Mohmad Khalid, Muhammad Iskandar Shah; Looi, Chee Kit; Khor, Ean Teng, 2021, "Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance", https://doi.org/10.21979/N9/NZ8N7M, DR-NTU (Data), V2, UNF:6:qUPyfXjS0D9VcYSbOtGU+Q== [fileUNF] Data set and R code script for the manuscript titled "Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance"
Appendix A.pdf Nov 16, 2021 - Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance Adobe PDF - 254.8 KB - MD5: 30927cf4d599c3ce2cd92bfd2466e43c Documentation
Online Supplementary Material.pdf Nov 16, 2021 - Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance Adobe PDF - 107.3 KB - MD5: 0cf0a56f0ab68008ae2444b1f6eb5721 Documentation
SEM_Measurement invariance_v2.R Nov 16, 2021 - Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance R Syntax - 28.9 KB - MD5: a550dcdef911dbd0ee54d11e58c905f5 Code Measurement invariance analyses

Transcript 5.docx

Jul 14, 2022 - Workplace learning in disruptive innovators: A knowledge management perspective

MS Word - 33.3 KB -

Transcript 6.docx

Jul 14, 2022 - Workplace learning in disruptive innovators: A knowledge management perspective

MS Word - 27.3 KB -

Transcript 7.docx

Jul 14, 2022 - Workplace learning in disruptive innovators: A knowledge management perspective

MS Word - 28.3 KB -

Transcript 8.docx

Jul 14, 2022 - Workplace learning in disruptive innovators: A knowledge management perspective

MS Word - 31.3 KB -

Transcript 9.docx

Jul 14, 2022 - Workplace learning in disruptive innovators: A knowledge management perspective

MS Word - 32.3 KB -

Liuyu Huang(Nanyang Technological University)

Jul 14, 2022

Appointment: Research Associate Research topics: • Workplace learning • Sharing economy • Data visualization • Bibliometrics

Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance

Nov 16, 2021

Puah, Shermain; Bin Mohmad Khalid, Muhammad Iskandar Shah; Looi, Chee Kit; Khor, Ean Teng, 2021, "Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance", https://doi.org/10.21979/N9/NZ8N7M, DR-NTU (Data), V2, UNF:6:qUPyfXjS0D9VcYSbOtGU+Q== [fileUNF]

Data set and R code script for the manuscript titled "Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance"

Appendix A.pdf

Nov 16, 2021 - Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance

Adobe PDF - 254.8 KB -

Documentation

Online Supplementary Material.pdf

Nov 16, 2021 - Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance

Adobe PDF - 107.3 KB -

Documentation

SEM_Measurement invariance_v2.R

Nov 16, 2021 - Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance

R Syntax - 28.9 KB -

Code

Measurement invariance analyses

Add Data

Share Dataverse

Link Dataverse

Reset Modifications