Emerging technologies (ETs) will most likely have a strong impact on education (starting with higher education), just like they have already had in so many economic and social areas. This paper is based on the results obtained in the project “My Future Colleague Robot”, an initiative that aimed to improve the competence of university teaching staff regarding the introduction of ETs in teaching practices at university level. In this paper, we identified the strengths and weaknesses, opportunities, and threats that are related to the adoption in higher education of the combination of two ETs: robotics together with artificial intelligence (AI). Additionally, we analyzed the perceptions of university-level teaching staff about the potential of introducing ETs in education. The empirical data presented here were collected using written essays from 18 university teachers and students. Deductive and inductive approaches with thematic analysis were used for the data analysis. The findings support the idea that previous ET-related experience can support positive attitudes and the implementations of ETs in university teaching; in this study, university teachers had optimistic expectations towards ETs, accepting them as part of teaching practice development, while discussion about the negative effects of ETs was negligible.

In this paper, we extend the concept of dynamic manipulability to evaluate the dynamic property of multifingered grasping systems consisting of a multifingered hand and a grasped object, and propose a measure of dynamic manipulability of multifingered grasping. Similar to the original dynamic manipulability, the proposed measure evaluates the mapping from a set of realizable joint torques to a set of resultant accelerations of the grasped object, which forms an ellipsoid under a constant internal force constraint. It is clearly shown that the internal forces not only affect the volume of the ellipsoid, but also the amount of offset of the ellipsoid, while the gravity forces simply induce an offset. A new measure, i.e., omnidirectionality, is introduced to add a penalty to the original manipulability measure, which simply evaluates the volume of the ellipsoid, depending on how much the ellipsoid is offset. Numerical examples by using a simple two-fingered robot hand are shown to demonstrate the effectiveness of the proposed measure.

This paper introduces a tactile rendering algorithm for wearable cutaneous devices that stimulate the skin through local contact surface modulation. The first step in the algorithm simulates contact between a skin model and virtual objects, and computes the contact surface to be rendered. The accuracy of this surface is maximized by simulating soft skin with its characteristic nonlinear behavior. The second step takes the desired contact surface as input, and computes the device configuration by solving an optimization problem, i.e., minimizing the deviation between the contact surface in the virtual environment and the contact surface rendered by the device. The method is implemented on a thimble-like wearable device.

Implementing an Emerging Technology (ET) is a difficult task due to people lacking ET-related knowledge and skills or having skeptical and negative attitudes towards the ET. As learners construct their understanding about an ET and develop related skills by actually passing through the ET Innovation Process (IP) stages (Awareness, Acceptance and Adoption), it could be useful to provide them with training that imitates certain IP stages. Using Artificial Intelligence Enhanced Robotics (AIER) as the example ET, we designed a two-day workshop to lead learners (n = 16) through the AIER IP Awareness stage, and a six-week training course with eight contact days to simulate the AIER IP Acceptance stage to learners (n = 10). Using online surveys and quantitative content analysis methods we confirmed that the workshop format increased the AIER-related self-confidence and general knowledge in 78% of participants, while the training course helped more than half of the participants to construct usable knowledge about a specific AIER and to see its possibilities in their specific work-place contexts. This paper is the pilot of using the Technology-Enhanced Learning Innovation Process (TELIP) model, first tested on a STEAM innovation, outside the educational context, for developing appropriate training approaches for specific ET IP stages.

Purpose: To identify the technical skills which, linked to digitalization processes, are required to achieve different types of business results. Design/methodology/approach: The Delphi method was applied, through the opinions of a group of Spanish experts, to identify the importance of certain skills for the advancement of digitalization and the implementation of Industry 4.0. Findings: The results show that: 1) skills in Robotics, the Internet of Things, Networks and Artificial Intelligence are necessary to achieve results in the management of company technical areas; 2) commercial management needs skills in Intelligent Systems, Big Data, Cybersecurity, Distributed Technology and Contents; and 3) for the business challenges of sustainable development, the environment and energy efficiency, the most needed skills are in Big Data, Intelligent Systems and Artificial Intelligence.Originality/value: The results are useful, firstly, in providing firms with a training and selection tool for the development of I4.0 and, secondly, in offering training centers criteria for drawing up their training programs.

Emerging technologies have a potential future impact on the developments in higher education and teaching practices at the universities. The paper is based on the project “My future colleague robot” that aims to improve the competence of university teachers in the implementation of Emerging Technologies (ETs) in the teaching practices at the university. In this paper, we identified the strengths and weaknesses, opportunities and threats that are related to the adoption of two ETs, robotics and Artificial Intelligence (AI), in higher education. Additionally, we analyzed the perceptions of faculty about these ETs. The empirical data was collected using written essays from 18 university teachers and students. Deductive and inductive approaches with thematic analysis were used for the data analysis. The findings support the idea that previous experience related to ETs can support positive attitudes and the implementations of ET in university teaching. University teachers had optimistic expectations towards ETs accepting them as part of teaching practice development, while discussion about the negative effects of ETs was negligible.