Navigating the Learning Landscape: Social Cognition and Task-Technology Fit as Predictors for MOOCs Continuance Intention by Sales Professionals

被引：0

作者：

Kamble, Aakash ^{[1
]}

Upadhyay, Nitin ^{[2
]}

Abhang, Nayna ^{[3
]}

机构：

[1] FLAME Univ, Pune, India

[2] Indian Inst Management, Jammu, India

[3] Medline Ind India Pvt Ltd, Pune, India

来源：

INTERNATIONAL REVIEW OF RESEARCH IN OPEN AND DISTRIBUTED LEARNING | 2024年 / 25卷 / 01期

关键词：

self-directed learning; MOOC; sales professional; social cognition theory; self-development; social recognition; task-technology fit; continued intentions; ACCEPTANCE MODEL; PERSPECTIVE; STUDENTS; ORIENTATION; PERCEPTIONS; MOTIVATIONS; IMPACT; MEDIA; USAGE;

D O I：

暂无

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

Massive open online courses (MOOCs) have gained popularity among sales professionals who use them for self-directed learning and upskilling. However, research related to their intentions to continue learning is scarce. Drawing from the social cognition theory, this research aimed to address this gap by investigating the role of task-technology fit, self-development, and social recognition in sales professionals' continued use of MOOCs. The study hinged on empirical research and used a survey to collect data from 366 sales professionals. The results suggest that task-technology fit, self-development, and social recognition play a significant role in sales professionals' continued use of MOOCs. The study has practical implications for organizations promoting employee learning and development. The findings provide valuable information for MOOC designers and providers to develop more effective courses that meet the needs of sales professionals.

引用

页码：24 / 44

页数：21

共 9 条

[1] Examining the Influence of Teaching Presence and Task-Technology Fit on Continuance Intention to Use MOOCs
Kim, Rang
Song, Hae-Deok
ASIA-PACIFIC EDUCATION RESEARCHER, 2022, 31 (04) : 395 - 408
[2] Examining the Influence of Teaching Presence and Task-Technology Fit on Continuance Intention to Use MOOCs
Rang Kim
Hae-Deok Song
The Asia-Pacific Education Researcher, 2022, 31 : 395 - 408
[3] Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives
Lin, Wen-Shan
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES, 2012, 70 (07) : 498 - 507
[4] Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model
Wu, Bing
Chen, Xiaohui
COMPUTERS IN HUMAN BEHAVIOR, 2017, 67 : 221 - 232
[5] Toward an understanding of the behavioral intention to use a social networking site: An extension of task-technology fit to social-technology fit
Lu, Hsi-Peng
Yang, Yi-Wen
COMPUTERS IN HUMAN BEHAVIOR, 2014, 34 : 323 - 332
[6] How does task-technology fit influence cloud-based e-learning continuance and impact?
Cheng, Yung-Ming
EDUCATION AND TRAINING, 2019, 61 (04): : 480 - 499
[7] Consumers' Purchase Intention of Organic Food via Social Media: The Perspectives of Task-Technology Fit and Post-acceptance Model
You, Jun-Jer
Jong, Din
Wiangin, Uraiporn
FRONTIERS IN PSYCHOLOGY, 2020, 11
[8] Predicting the acceptance of MOOCs in a developing country: Application of task-technology fit model, social motivation, and self-determination theory
Khan, Ikram Ullah
Hameed, Zahid
Yu, Yugang
Islam, Tahir
Sheikh, Zaryab
Khan, Safeer Ullah
TELEMATICS AND INFORMATICS, 2018, 35 (04) : 964 - 978
[9] Learning Outcomes of Educational Usage of Social Media: The Moderating Roles of Task-Technology Fit and Perceived Risk
Sabah, Nasser M.
Altalbe, Ali A.
SUSTAINABILITY, 2022, 14 (14)

← 1 →