Gamification of E-Learning in African Universities

Gamification in education is a strategy of motivating and engaging students by integrating game design features into the instructional process. Although there is a growing body of scientific evidence supporting the effectiveness of gamification in the educational setting, some of the evidence is inconclusive and insufficient, especially in developing nations. The purpose of this study is to integrate the technology acceptance model and task technology fit to investigate instructors' intention to use gamified online learning. A sample of 50 participants across various African institutions was involved in this study. Structural equation modelling implemented via partial least squares (PLS) is used to test the research hypotheses. The results revealed that intention to use gamified online learning was significantly and positively influenced by task technology fit, perceived usefulness, and attitude. Notably, subjective norms, facilitating conditions, and computer anxiety failed to predict behavioural intention. The authors discuss the implications of the findings and propose future directions.

Voice Assistant vs. Chatbot – Examining the Fit Between Conversational Agents’ Interaction Modalities and Information Search Tasks

Owing to technological advancements in artificial intelligence, voice assistants (VAs) offer speech as a new interaction modality. Compared to text-based interaction, speech is natural and intuitive, which is why companies use VAs in customer service. However, we do not yet know for which kinds of tasks speech is beneficial. Drawing on task-technology fit theory, we present a research model to examine the applicability of VAs to different tasks. To test this model, we conducted a laboratory experiment with 116 participants who had to complete an information search task with a VA or a chatbot. The results show that speech exhibits higher perceived efficiency, lower cognitive effort, higher enjoyment, and higher service satisfaction than text-based interaction. We also find that these effects depend on the task’s goal-directedness. These findings extend task-technology fit theory to customers’ choice of interaction modalities and inform practitioners about the use of VAs for information search tasks.

Using Structural Equation Modeling to Assess Online Learning Systems’ Educational Sustainability for University Students

The purpose of this study was to investigate the factors that influence the use of e-learning among students in higher education during the Corona Virus disease, during the 2019 season (COVID-19). A poll of 395 students from the student’s university was used to conduct the research. The study’s theoretical foundation was an expanded Technology Acceptance Model (TAM), which included task-technology fit and students’ engagement, as well as external elements such as experience (EXP), technology anxiety (TEA), and facilitating conditions (FC). The suggested model was tested and evaluated using SEM-PLS. The investigation demonstrated that the suggested TAM-based scale effectively describes factors impacting students’ use of E-learning during the pandemic. According to the findings, students’ engagement (SEN), EXP, TEA, and FC have a favorable impact on task–technology fit (TTF) and perceived ease of use (PEOU), resulting in a good impact on TTF and usage of an e-learning system for educational sustainability (EA). Finally, the TTF fit and convenience of use of eLearning in education have a positive impact on the behavioral intention to use an e-learning system for educational sustainability and the adoption process. As a result, higher education institutions should use eLearning as a sustainability learning strategy.

An Empirical Study on How Livestreaming Can Contribute to the Sustainability of Green Agri-Food Entrepreneurial Firms

During the COVID-19 pandemic, digital technology has been used in all aspects of the agricultural field. How to seize the opportunity to achieve the production-marketing connection is increasingly becoming a top concern for green agri-food enterprises. Based on the theory of a task–technology fit, this study analyzes the fitness between livestreaming e-commerce and green agri-food. More specifically, the task characteristics cover the seasonality, locality, and eco-friendliness of green agri-food, and the technology characteristics cover the responsiveness, interactivity, and entertainment of livestreaming e-commerce. Using data of a sample of 574 green agri-food entrepreneurial firms collected through a web-based questionnaire, we preform structural equation modeling (SEM) analysis and find that the locality and eco-friendliness of green agri-food, the responsiveness, interactivity, and entertainment of livestreaming e-commerce have a positive effect on the fit of green agri-food livestreaming e-commerce. Moreover, the fit of green agri-food livestreaming has a positive effect on firm performance and the intention to adopt livestreaming e-commerce. This study also demonstrates that perceived corporate social responsibility has a moderating effect on the relationship between the fit of livestreaming of green agri-food and the intention to adopt livestreaming e-commerce. This study extends prior research on the task–technology fit into livestreaming e-commerce companies and provides insights into our understanding of successful adoption of livestreaming e-commerce.

ANALYSIS OF THE TASK-TECHNOLOGY FIT MODEL APPLIED TO WHATSAPP AS A PREFERENCE OF YOUNG USERS OF MOBILE INSTANT MESSENGERS

The purpose of this article is to analyze the technology-task adjustment model applied to WhatsApp as a preferred communication method by young Mobile Instant Messengers (MIM) users. Thus, we conducted a survey (n=567) and a multivariate data analysis through Structural Equation Modeling. Only one hypothesis of the model was rejected showing that hedonic needs do not influence needs perceived by users. Users do not realize pleasure as a need when it comes to MIMs with communication-oriented features and is not exclusively for fun. We also found that the behavioral profile of young users to perceive the importance of motivational needs, technological characteristics, perceived needs, satisfaction, and privacy, to generate the intention to continue using the mobile communication tool.

Students’ Performance in Online Learning Environment: The Role of Task Technology Fit and Actual Usage of System During COVID-19

The 2019 Pandemic has forced students to take online classes, increasing their stress levels and negatively impacting their academic performance. This issue urges the development of a mechanism to make online learning more effective in this nerve-racking time. Therefore, the present study has integrated the task technology fit (TTF) model and the DeLone and McLean Model of Information Systems Success (DMISM) to address the stated issue. The data were collected from 330 and 326 students of top-ranked public and private universities of Punjab, respectively. The theoretical framework was analyzed with the help of structural equation modeling (SEM) using Analysis of Moment Structures (AMOS). The findings indicate that overall quality positively predicts performance through the mediating role of user satisfaction and TTF. The overall quality also positively elevates performance through the mediating role of user satisfaction and actual usage of the system. Moreover, perceived usefulness proved to be a moderator between overall quality and user satisfaction. Finally, the expected practical and theoretical implications have also been discussed.

Examining internet banking user’s continuance intention through the lens of technology continuance theory and task technology fit model

Purpose The long-term success of internet banking (IB) services is connected with continuous use. Therefore, examining factors which influence IB user continuance intention is important. Grounded in technology continuance theory, bank transparency and task technology fit (TTF) model, the purpose of this study is to develop a unified technology continuance model to investigate IB user continuance intention. Design/methodology/approach The research model was empirically tested with 348 responses. Respondents included in this study had prior experience with IB services. For hypotheses testing, the structural equation modelling approach was used. Findings Findings indicate that the research model has substantial power in explaining IB user continuance intention. Importance performance matrix analysis revealed that bank transparency had the highest importance in determining IB user continuance intention. Therefore, factors like user satisfaction and perceived usefulness have shown a medium level of importance in determining IB user continuance intention. Satisfaction is influenced by perceived usefulness and confirmation and established a significant impact on IB user continuance intention. Practical implications The findings of this research are useful for bank managers and policymakers to develop and design IB services according to user’s expectations. Results demonstrate that expectation confirmation and perceived usefulness are antecedents of IB user satisfaction and IB user continuance intention. In addition to that bank, transparency has shown a significant effect on user expectation and IB user continuance intention. These findings established that accuracy in sharing bank information and clarity in transaction charges encourage the user to continue the use of IB services. Originality/value The current study develops a unified technology continuance model based on the TTF model and technology continuance theory and investigates IB user continuance intention. Moreover, bank transparency is added in the technology continuance model and established a significant impact towards user expectation confirmation and continuance intention. These findings contribute to the limited body of research in the context of IB user continuance intention and enrich information system literature.

Satisfaction With ERP System Implementation

While many studies explain factors influencing the success of ERP implementation, little is known about the system outcome to satisfy user expectations based on the concepts of task-technology fit and person-task fit. The study examines the effects of fits between user interfaces, task interdependence, and user knowledge on system utilization and performance impacts leading to user satisfaction with ERP system implementation. Based on the structural equation modeling analysis and two-way interaction test results, a user interface dampens the positive effect of task interdependence on task-technology fit while it strengthens the positive effect of user knowledge on task-technology fit. Task interdependence dampens the positive effect of user knowledge on system utilization. The results provide guidance on how to enhance the system impacts on user performance and encourage the system usage resulting in user satisfaction with the ERP system implementation. The paper provides detailed discussions of the results, the implications for theory and practices, and the study limitations.