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This paper aims to present part of the work of an ongoing research project that is looking at socio‐ cultural and technological developments from a mobile technology convergence view; in order to show how culturally aware convergence developments in mobile technology can be adopted and employed for the betterment of society.

The paper presents a scenario for a mobile technology enabled learning environment in support of the conventional learning approach with a focus on enabling parental involvement and contribution to the daily learning objectives of their children and hence enhancing a quality learning experience. It further critically discusses issues of interface design – at both the device and application levels – that will have an impact on the quality of e‐learning, with a focus on mobile technology.

The paper shows how interface design can positively enhance the quality defining characteristics of learning in an e‐learning environment. Ways of achieving these characteristics of learning through effective e‐learning are reported. This is done by addressing requirements for quality‐learning through effective interface‐design considerations, towards meeting the overall quality requirements of learning that should be intrinsic to a holistic e‐learning environment. The value of human computer interaction and the critical factors of promoting productive interaction are addressed.

There are several factors affecting quality of e‐learning as a tool and approach to flexible and independent learning. The advent and use of mobile technology has been investigated in this work from a socio‐cultural and technological perspectives in two continents. The limitations lie in the depth of investigations and how far the findings can be applied to the diversity of learners.

As the effects of cultures and the rapid technological advancements take toll on teaching and learning the findings reported in this paper have far reaching implications for learners from different cultures and also for attempts at bridging existing digital divide.

The approach adopted in the research is unique by virtue of new findings and ideas presented. The paper highlights the opportunities for mobile devices and technology to play a role in the development of communities through technology aided learning (e‐learning), with a focus on e‐learning systems and technology requirements for delivering a quality learning experience.

This paper aims to report on the second half of a two‐part study that identified relevant content for safety audit training in small businesses. The specific aim of the paper is to determine the preferred learning styles and approaches of managers in these businesses in order to identify some principles which could be used to tailor training to meet their particular learning needs.

Participants in the study came from three relatively high‐risk industries – road transport, construction, and the motor trade – producing a sample size of 102. A self‐report questionnaire was distributed via trade magazines.

Very few differences were found between the three industries. Most differences were between road transport and the other two industries. Managers in the road transport industry have a lower preference for learning by listening and are less likely to be sequential learners than managers in the motor trade industry.

Small business managers are systematic, hard‐working, pragmatic and prefer less formal modes of learning. These characteristics have implications for the structure and context of training programmes and the nature of the training materials.

The four learning profiles that emerged from the analysis in the paper provide a clear picture of the small business managers in the three industries studied.

Teaching by demonstration (TbD) is a promising way for robot learning skills in human and robot collaborative hybrid manufacturing lines. Traditionally, TbD systems have only concentrated on how to enable robots to learn movement skills from humans. This paper aims to develop an extended TbD system which can also enable learning stiffness regulation strategies from humans.

Here, the authors propose an extended dynamical motor primitives (DMP) framework to achieve this goal. In addition to the advantages of the traditional ones, the authors’ framework can enable robots to simultaneously learn stiffness and the movement from human demonstrations. Additionally, Gaussian mixture model (GMM) is used to capture the features of movement and of stiffness from multiple demonstrations of the same skill. Human limb surface electromyography (sEMG) signals are estimated to obtain the reference stiffness profiles.

The authors have experimentally demonstrated the effectiveness of the proposed framework. It shows that the authors approach could allow the robot to execute tasks in a variable impedance control mode with the learned movement trajectories and stiffness profiles.

In robot skill acquisition, DMP is widely used to encode robotic behaviors. So far, however, these DMP modes do not provide the ability to properly represent and generalize stiffness profiles. The authors argue that both movement trajectories and stiffness profiles should be considered equally in robot skill learning. The authors’ approach has great potential of applications in the future hybrid manufacturing lines.

The elearn2work study of learning styles in the context of small to micro firms' (SMFs) and their perceived satisfaction has identified some important finding specific to e‐learning content design, delivery and international standards development.

The method of research adopts a deductive rather than an inductive approach via descriptive profiling and multivariate statistical analysis.

From the elearn2work study we have identified tentative findings that indicate e‐learning inequity for many SMF learners including employees and managers. From our research there is a clear gap between the profile of SMF learners, in the context of their learning style, and the typical content that is currently being designed for e‐learning provision. The sector is driven by analytic type educators/trainers who are frequently not a reflection of SMF learners.

It could be argued that many SMF workers are currently being socially excluded from e‐learning provision through pedagogy inequity when considering the lack of learning styles support in work‐based learning practice.

Students have learning difficulties, mainly in processes that involve attention and interpretation of written or spoken language. Technological tools allow to create computational platforms with adaptation aspects depending on the student’s characteristics. It is also important to highlight the progress of the measurement of cognitive processes such as attention through NeuroSky’s MindWave EEG sensors. This paper aims to present the results of analyzing attention levels of children with learning difficulties, based on the acquired brain waves. As a final result, an adaptive computational system that displays educational activities regarding educational profiles of children is obtained.

The Kamachiy–Idukay platform was chosen to make the validation. The platform generates the educational activities according to the students’ profile. The validation phases were identification of the test environment, the first environment required a scenario that involved students with learning difficulties, to verify the functionality of the system, when analyzing cases of the students with learning difficulties; identification of two validation criteria, type of educational activity and attention difficulties of the students; and analysis of the brain signal when children interact with the educational content.

The adaptation of contents that include music and animations generate higher levels of attention in students with difficulty. The analysis of signals from the NeuroSky sensor to determine the attentional levels in children allowed a generation of content adapted to the characteristics of the difficulty in each child.

For the validation, it was necessary at the beginning of the activity to determine the stability of the signal emitted by the NeuroSky sensor. Two cases were studied in children with difficulty and their measure of attention versus adaptive contents.

A k-means algorithm was used to establish the attention levels of the children.

Children with learning difficulties have different learning styles, which implies an adaptation of content that generates an attentional process according to their characteristics.

Evaluation content adaptation taking into account the signal brain sensor NeuroSky for learning process. The signal brain of the student when interacting with the activities is include in the student profile.

This research examined the presence of career orientation profiles by investigating how young workers combined protean career orientation attitudes, motivation to learn to develop one's career and an optimistic future perspective on their career. It explored how a differentiated endorsement of these attitudes and motivation (i.e. career orientation profiles) were associated with the adoption of multiple career-enhancing behaviors, namely proactive career behaviors (i.e. career planning, networking and skill development) and learning behaviors with technologies.

Latent profile analysis was conducted among young individuals starting their career (N = 767) and found four distinct profiles.

The first profile revealed that 17.2% of workers in this sample were displaying low levels in protean career orientation, motivation to learn and optimistic future time perspective (profile 1). Two differentiated profiles showed either low levels of protean career orientation and high levels of motivation to learn (profile 2) or high levels of protean career attitudes and low levels of motivation to learn (profile 3). These profiles presented an average level of future time perspective and represented 13.8 and 40.6% of the sample. Finally, 28.4% of the sample showed high levels on all these variables (profile 4).

Only young workers who showed high levels on all these indicators also presented high levels of proactive behaviors and learning with technologies. The other three profiles were associated with suboptimal levels on these outcomes. Taken together, these results offer new insights into the psychological state of mind of workers most adapted to succeed in a modern career.

Human resource development practitioners and others do not appear to share a common underlying framework for, and understanding of, “learning style”. Argues that learning style is but one construct which, along with learning preferences and cognitive styles, may be included under the umbrella term “personal style”. Reviews each aspect of the suggested personal style framework and considers its relationship to learning performance at the reaction, learning, behaviour and results levels. Describes the instruments which may be used for profiling personal style. Suggests that personal styles profiling is of value to HRD practitioners because it may enable them to: identify their own styles; become aware of any bias or imbalance in the training and learning methods which they employ; design and develop learning events which accommodate, or at least acknowledge, the personal styles of the learners.

Research on knowledge creation within eSports learning is scarce. This study extends the understanding of competition-oriented collaborative learning in eSports by examining the relationship between the dynamics of knowledge creation modes and the continuum of the motivational profile, along with the moderating effects of mutualistic co-presence therein.

Participants were recruited from the community of massively multiplayer online gamers (MMOGs). Through a quantitative survey, their motivations (i.e. self-extrinsic, self-intrinsic, peer-extrinsic and peer-intrinsic motivations), knowledge creation involvements (i.e. internalization, externalization, combination and socialization) and perception of mutualistic benefit of self and peers were captured for hypothesis testing.

Significant and positive direct relationships were observed between four motivations and four knowledge creation modes. The mutualistic co-presence positively moderated the positive relationship between the self-extrinsic, peer-extrinsic and peer-intrinsic motivations and socialization. When mutualistic self-benefit were outweighed, peer-extrinsic motivated gamers became less likely to perform internalization, whereas self-extrinsic and peer-extrinsic motivated gamers were less likely to perform combination.

This study is among the first to rationalize the relationship between motivational profile and the dynamics of knowledge creation in eSports learning. The conceptualization of the new construct – mutualistic co-presence – using the ecological concept of symbiosis is uncommon in prior literature. The findings also demonstrate that the four modes of knowledge creation in eSports learning are continuous and interwoven; they can be initiated at any point and do not necessarily occur in a specific sequence.

The purpose of this paper is to present a method which enables a robot to learn both motion skills and stiffness profiles from humans through kinesthetic human-robot cooperation.

Admittance control is applied to allow robot-compliant behaviors when following the reference trajectories. By extending the dynamical movement primitives (DMP) model, a new concept of DMP and stiffness primitives is introduced to encode a kinesthetic demonstration as a combination of trajectories and stiffness profiles, which are subsequently transferred to the robot. Electromyographic signals are extracted from a human’s upper limbs to obtain target stiffness profiles. By monitoring vibrations of the end-effector velocities, a stability observer is developed. The virtual damping coefficient of admittance controller is adjusted accordingly to eliminate the vibrations.

The performance of the proposed methods is evaluated experimentally. The result shows that the robot can perform tasks in a variable stiffness mode as like the human dose in the teaching phase.

DMP has been widely used as a teaching by demonstration method to represent movements of humans and robots. The proposed method extends the DMP framework to allow a robot to learn not only motion skills but also stiffness profiles. Additionally, the authors proposed a stability observer to eliminate vibrations when the robot is disturbed by environment.

This paper aims to highlight some learning and teaching challenges in relation to universities and colleges in the Gulf region, including students' learning preferences, and cultural aspects. It explores the sequential‐global learning styles profile of undergraduate students as part of a continuous research in Information Systems Design with a particular focus on the design of Interactive Learning Systems (ILS).

The paper examines the learning style profile of undergraduate students for a cohort of Management Information Systems at a regional university in the UAE. It uses the Index of learning styles instrument as a tool for measuring the sequential‐global learning styles dimension. Also, the paper conducts a literature review of different aspects related to current challenges facing undergraduate students in the Gulf region as well as design principles related to the interactivity of learning systems.

The results show overall equal tendency towards both the sequential and global styles, different from a previous paper conducted in UK university. The paper highlights some students' differences that should be catered for in ILS design.

The paper is expected to provide further insights into some of the challenges facing many students doing their undergraduate degrees as well as the importance of a carefully balanced design of ILS (balance and bend model) to cater for students' different preferences and needs. A discussion and recommendations on how these findings can be reflected on the design of ILS are provided.