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This paper aims to develop indicators of happiness in learning of the Thai open university (TOU)'s undergraduate students.

Sampling for the study was comprised of two groups. Group I comprised eight lecturers who are experts in their disciplines and six students who were purposively sampled. The focus group was used to validate the appropriateness of the indicators. In Group II, 332 students were engaged in a multistage sampling process. The responses were analyzed using descriptive statistics, coefficient correlation, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

The indicators of happiness in learning of undergraduate students of TOU were classified in six categories. These included satisfaction with learning environment (five indicators), learning anxiety (five indicators), satisfaction with learning (five indicators), enthusiasm to learn (six indicators), self-satisfaction (six indicators) and readiness to learn (seven indicators). The six categories explained happiness in learning of undergraduate students of TOU at the 65% and fit empirical data.

The TOU can use the indicators for the assessment of happiness in learning of its students as well as guidelines for the improvement of its student learning environments.

There have been very few studies on indicators of happiness in learning of TOU students. Most were done at the basic education level. This study disclosed the six factors affecting happiness in learning of TOU students; therefore, it should inspire and draw attention of many in the field of higher education distance learning.

This study aims to identify the most significant factors that influence acceptance of e-learning in India. As e-learning has gained popularity in the wake of the COVID-19 pandemic and continues to be one of the most sustainable methods of education, it is pertinent to examine learners' perception towards its acceptance. There is limited literature available on this subject in India, especially factoring in impact of the pandemic.

This study empirically analyses data of 331 adult e-learners in India, who have enrolled for one of the following e-learning formats: higher education, private coaching, test preparation, re-skilling and online certifications, corporate training and hobby and language-related learning. Their perception is examined on the basis of a model developed using the Unified Theory of Acceptance and Use of Technology model. Data are analysed through structural equation modelling using SPSS and AMOS statistical tools.

The result of the study shows that Infrastructure Dependability, Effectiveness of Design and Content of Courses and Student's Competency with Computers are the top three factors impacting e-learning acceptance in India.

This study makes several theoretical contributions. Additionally, research findings and recommendations will facilitate education providers, corporates in the education industry and policymakers to focus on the significant areas for enhancing the acceptance of e-learning.

This study identifies and confirms important factors that influence e-learning acceptance and suggests opportunities for further in-depth research and analysis.

The literature includes several studies that define different critical success factors (CSF) which have to be considered to support the implementation of technology-enhanced learning (TEL) approaches. An analysis of such studies revealed that (1) regional differences seem to determine the CSF for TEL approaches, (2) certain CSF are relevant for TEL approaches in general, and (3) professionals in higher education determine which influential factors they consider when implementing TEL approaches. Thus, the question arises: in general, which influential factors do professionals in Austrian and German institutions of higher education actually consider when implementing TEL approaches?

The study is a quantitative research approach based on survey data.

The results show that certain influential factors seem to be generally important, such as the factors of respecting learning success or motivation. However, the outcome of the study also indicated that different moderating variables like experiences and personal relevance affect the professionals’ choices.

The originality and value are in the approach to identify generally important influential factors for the implementation of TEL approaches in Austrian and German institutions of higher education.

The purpose of this paper is to examine the relationship among training design, trainee motivation and work environment on the transfer of learning for teachers enrolled in a continuing professional education (CPE) training program and the confirmation of potential positive, predictive relationships of trainee motivation, work environment and training design to transfer of learning. This study investigated the contribution of training efficiency and relevance as measured by the training design; work environment as measured by work autonomy, work complexity and work variability; and trainee’s motivation of training (learning- and job-oriented) to the transfer of knowledge and skills from the training program to their workplace. Both direct and indirect effects of mentioned components on the learning transfer were explored.

This study included 160 teachers working in high-needs schools with large numbers of English learners (ELs) Southwest USA. Teachers in this study primarily needed professional development to empower them and enhance their instructional capacity for ELs and economically challenged students. During the recruitment, participants completed a demographic information (e.g. gender, ethnicity, number of years teaching, age, educational background) survey.

A mediation model with training design as the mediating factor was developed and analyzed. The results revealed that training design fully mediated the relationship between trainees’ work environments and the transfer of knowledge, skills and attitude acquired from the training to their workplace. Furthermore, it partially mediated the relationship between learning-oriented motivation and the transfer of learning. These findings further amplify the significance of CPE program training design and foster important considerations for future research regarding the isolation of specific training design aspects that significantly contribute to the mediation of these relationships.

Considering the significance of learning transfer in developing professional knowledge and skills for target employees and trainees, confirming the mediating effects of training design on training transfer holds critical implications for future research. Specific and purposeful attention needs to be given to the design of CPE training. Investigations into the effects of training design and successful elements such as the training platform (online, hybrid or in-person), sample size, group structure, facilitation and participant demographics are warranted.

The finding of this research provides a preliminary guide for scholar-practitioners. Results of the study confirmed the role that learning-oriented motivation, job-oriented motivation, work variability or flexibility, work complexity and training design play in transfer of learning. In practice, training professionals will be more comfortable pinpointing the factors that lead to the transfer of learning or the lack of it.

Learning transfer has been found to be imperative for target employees and trainees to develop professional knowledge, skills and attitudes. Results of this study reveal variables that promote the positive transfer of learning to the workplace.

Learning as the way in which labor acquire new knowledge and skills has important strategic implications for the competitive advantage of an organization. The purpose of this paper is to present an agent-based modeling (ABM) approach to investigate the learning behavior of workers. The effect of interactions among different workers as well as the factors affecting the workers’ learning behavior is assessed using the proposed ABM approach.

For this purpose, the processes through which the competency value of worker is changed are understood and the workers’ learning behavior is modeled, taking account of various influencing factors such as knowledge flow, social ability to teach and forgetting factor.

The proposed model is implemented on a real steel structure project to evaluate its applicability and performance. The variation in the competency value of different workers involved in the project is simulated over time taking account of all the influencing factors using the proposed ABM approach.

In order to assess the effect of interactions among welders as well as the welders’ characteristics on their learning behavior, the competence value of different welders is evaluated.

This research presents an ABM approach to investigate the workers’ learning behavior. To evaluate the performance of the proposed ABM approach, it was implemented on a real steel structure project. The learning behavior of different welders (agents) was simulated taking account of their interactions as well as the factors affecting the welders’ learning behavior. The project involved the welding of a 240-ton steel structure. The initial project duration was estimated as 100 days. In this project, it has been planned to execute the welding process using three different welders namely welder A, B and C.

Students' satisfaction with e-learning outcomes is a vital component in determining the adoption of e-learning systems. Understanding the antecedent factors impacting students' satisfaction with e-learning outcomes helps decision-makers at the higher education to take the necessary actions to enhance the quality of students' performance, especially during the exceptional times, such as the COVID-19 pandemic.

This paper aims to determine and analyse the antecedent factors influencing students' satisfaction with e-learning outcomes during the pandemic. Structural equation modelling (SEM) is used to analysis a proposed research model.

The SEM results show that digital communities in e-learning, information technology (quality and accessibility) and the online course design quality directly influence students' satisfaction with e-learning outcomes. More interestingly, results show that the COVID-19-related factors (1) awareness of the COVID-19, (2) perceived challenges (negatively) and (3) the educational institutions' preparedness also influence e-learning outcomes.

The results suggest that the decision-makers at the educational institutions should consider adopting a blended learning system approach to deliver e-learning during the emergency, such as the COVID-19 outbreak situation.

This is one of the first studies in higher education context, which seek to identify the antecedent factors that influence students' satisfaction with e-learning outcomes during the COVID-19 pandemic.

During the COVID-19 pandemic, educational institutions were forced to shut down, causing massive disruption of the education system. This paper aims to determine the critical factors for the intention to participate in e-learning during COVID-19.

Data were collected by surveying 131 university students and structural equation modelling technique using PLS-SEM was employed to analysis the data.

The results showed that the COVID-19 related factors such as perceived challenges and COVID-19 awareness not only directly impact students' intention but also such effects are mediated through perceived usefulness and perceived ease of use of e-learning systems. However, the results showed that the educational institution's preparedness does not directly impact the intention of students to participate in e-learning during COVID-19. The results also showed that the gender and length of the use of e-learning systems impact students' e-learning systems use.

These results demonstrated that, regardless of how well the educational institutions are prepared to promote the use of e-learning systems, other COVID-19-related challenges play a crucial role in forming the intention of students to participate in e-learning during the COVID-19 pandemic. Theoretical and practical implications are provided.

The onus of this study was to find out the role played by virtual learning environment factors on students' satisfaction during the COVID-19 period in Nigeria. A survey was carried out on students in higher education institutions in Nigeria to actualize this purpose.

Simple random sampling techniques with the aid of Krejcie and Morgan's (1970) sample determinant and the Snowball sampling technique were adopted to sample 270 students in higher education institutions in Nigeria. An adapted questionnaire was used. Cronbach alpha coefficients were calculated for the two sections of the independent and dependent variables. Virtual learning environment factors yielded 0.89, while students' satisfaction yielded 0.87. Data were analyzed using descriptive statistics, Pearson product–moment correlation, two-way ANOVA and linear regression analysis.

The results of the ANOVA, F (df 4, 265) = 50.905, p < 0.000, indicate a statistically significant relationship (stronger than 0.05) between the independent variables (virtual learning environment factors) and the dependent variable (students' satisfaction). It was found among others that instructors' support and collaboration factors predicted students' satisfaction with virtual learning experiences during the COVID-19 period.

Virtual learning during COVID-19 caught both lecturers and students unprepared. Most developing countries especially Africans were used to the traditional face-to-face learning, more so, the use of virtual means to learn was still at a nascent stage. This study, therefore, contributed to the role of the learning environment in virtual learning satisfaction.

This study clarifies the factors that foster individual innovative behaviour in the public sector by examining the effects and roles of empowering leadership, work group cohesiveness and individual learning orientation. This study also explores the direct effect of empowering leadership on work group cohesiveness and individual learning orientation, the influence of work group cohesiveness on individual learning orientation and the mediating roles of work group cohesiveness and individual learning orientation.

Data were collected from an online survey of respondents working in a public sector organization. Partial least squares structural equation modelling and mediation analysis by the bootstrap method were used for the data analysis.

Empowering leadership and individual learning orientation had significant direct effects on individual innovative behaviour. Both empowering leadership and work group cohesiveness have significant direct effects on individual learning orientation. Empowering leadership was positively related to work group cohesiveness. The mediation analysis revealed that individual learning orientation mediates the relationships between empowering leadership and individual innovative behaviour and between work group cohesiveness and individual innovative behaviour.

The study focuses on three factors that foster individual innovative behaviour in a public sector organization.

This study offers new insights into the factors that foster individual innovative behaviour in the public sector. The findings reveal the importance of using a balanced leadership style and encourage learning in the workplace for individual innovativeness by public leaders.

The purpose of this paper is to investigate and quantify the impact of product complexity, including architectural complexity, on operator learning, productivity and quality performance in both assembly and disassembly operations. This topic has not been extensively investigated in previous research.

An extensive experimental campaign involving 84 operators was conducted to repeatedly assemble and disassemble six different products of varying complexity to construct productivity and quality learning curves. Data from the experiment were analysed using statistical methods.

The human learning factor of productivity increases superlinearly with the increasing architectural complexity of products, i.e. from centralised to distributed architectures, both in assembly and disassembly, regardless of the level of overall product complexity. On the other hand, the human learning factor of quality performance decreases superlinearly as the architectural complexity of products increases. The intrinsic characteristics of product architecture are the reasons for this difference in learning factor.

The results of the study suggest that considering product complexity, particularly architectural complexity, in the design and planning of manufacturing processes can optimise operator learning, productivity and quality performance, and inform decisions about improving manufacturing operations.

While previous research has focussed on the effects of complexity on process time and defect generation, this study is amongst the first to investigate and quantify the effects of product complexity, including architectural complexity, on operator learning using an extensive experimental campaign.