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PurposeThis paper seeks to assess the level of impact of COVID-19 pandemic on professional practice for members of professional organisations and the general public in the conduct of business. Investigations into practice using events, attendance records and registered views are carried out. The aim is to identify the challenges and actions being taken to mitigate against them in moving from physical (face-to-face) to virtual (online) mode of operations.Design/methodology/approachThe past two years have seen a complete change in the way we live from life at home, at work and in education. This has impacted the way professional organisations now conduct business including the need to revise ways of upskilling and sustaining practice. Core to all of this is the role of computing and communication for all persons in all works of life. The current study focusses on professional activities and support provided to members of British Computer Society (BCS), The Chartered Institute for IT. The authors examine the events provided, the conduct support provided to members and the general public. The method includes use of surveys of all stakeholders and analysis of data obtained.FindingsThe onset of COVID-19 pandemic was perceived as a real shock for everyone everywhere. Contrary to expectations, faced with the reality of having to do everyone online, the current study found that there were observed increased in the number of activities of professional organisations worldwide. Most interesting is that fact that the number of people participating in these events was found to be increasing using e-learning and other associated online tools and resources. Participants of these events were no longer restricted to local members but widespread globally. There was the appetite for more events to be put up and willingness for more individual and groups to volunteer and/or participate.Research limitations/implicationsThe limitations of current study are that only a few of the many activities have been investigated in this one professional body, BCS, The Chartered Institute for IT. The fact that more events are now being carried out for the many groups and branches implies a lot more digital data would be available for further study to inform developments of members and the general public.Practical implicationsThe impact of COVID-19 pandemic is a huge and evolving. It remains and presents a complicated case for the world to deal with. Amongst the many realities is that living life online has become a new normal and one everybody must learn to adjust to. Professional organisations such as the BCS would need to think of not only their members but also the general public and how well society and business can be sustained going forward. This involves considering developments of educational resources and appropriate platforms to meet the needs of the public, private and the voluntary sectors in society.Social implicationsDue to restricted physical (face-to-face) interactions, previously developed processes would require reviewing. New informed policies would need to be developed and implemented by professional organisations on revised practices resulting from impact of the pandemic. The emanating global participation from local activities presents challenges involving time, space (geographical location) and cultural differences. The digital divide that exists in society and access to the fast and reliable Internet services are also worth considering.Originality/valueThe impact of COVID-19 on professional practice applied to education and business is important in the face of the many and varied challenges everyone is facing everywhere in the world. This has been intense at home and at work globally. Although the true cause is yet to be established, it is important that ways to address challenges and continue with life are found and implemented. This paper establishes some of the impacts and present recommendations that are useful in forging ahead for people in the information technology profession.

Machine learning has been extensively used for analyzing spectral data in food quality management. However, collecting high-quality spectral data from miniature spectrometers outside the laboratory is challenging due to various factors such as distortions, noise, high dimensionality, and collinearity. This paper presents an in-depth analysis of food datasets collected from miniature spectrometers to evaluate the data quality and characteristics, by focusing on a case study of olive oil quality check, where various machine learning models were applied to differentiate pure and adulterated olive oil. Furthermore, the impact of pre-processing techniques on data distortions was studied. It presents a comprehensive pipeline, including data pre-processing, dimension reduction, classification, and regression analysis, and deploys different algorithms for comparative classification and regression analysis. The model performances were assessed using 2 separate methods: tenfold cross-validation on an entire dataset with 10% random testing, and an entire test set collected in different environments (multi-session validation). The first validation approach reached classification rates of up to 96.73%, while the second achieved 83.32%. These results demonstrate that cost-effective miniature spectrometers augmented with a suitable machine learning pipeline could execute classification tasks on par with non-portable and more expensive spectrometers. Furthermore, the study highlights the requirement of specialized algorithms to handle different ambient conditions affecting data acquisition and to eliminate performance gaps, making miniature spectrometers suitable for in situ scenarios. This work extends previous research to enable consumers becoming the first line in the defense against food fraud.

Scholarly interests in developing personalized learning analytics dashboards (LADs) in universities have been increasing. LADs are data visualization tools for both teachers and learners that allow them to support student success and improve teaching and learning. In most LADs, however, a teacher-centric, institutional view drives their designs, treating students only as passive end-users, which results in LADs being less useful to students. To address this limitation, we used a card-sorting technique and asked 42 students at a university in Northern Ireland to construct dashboards that reflect their priorities. Using a situated theory of learning as a lens and with the help of multiple qualitative methods, we collected data on what constitutes useful dashboards. Findings suggest that situated learning data sets, such as information on how students learn by talking and listening to others in their communities, need to be integrated into LADs. Students preferred to see the inclusion of qualitative narratives, self-directed learning data and financial information (money spent versus resources utilized) in LADs. As well as raising new questions on how such LADs could be designed, this study challenges institutional overreliance on measurable digital footprints as proxies for academic success. We call for recognizing the wider social learning that happens in landscapes of practice so that LADs become more useful to students.

PurposeMassive open online courses (MOOCs) have received wide publicity and many institutions have invested considerable effort in developing, promoting and delivering such courses. However, there are still many unresolved questions relating to MOOCs and their effectiveness in a blended-learning context. One of the major recurring issues raised in both academic literature and in the press about MOOCs is the consistently high dropout rate of MOOC learners.Design/methodology/approachIn this study, we applied mixed methods as an exploratory case study, which prioritised the quantitative and qualitative approaches for the data collection processes. The data were collected using a MOOC Online Self-regulated Learning Questionnaire (MOSLQ) adapted and created from an existing measuring instrument. The quantitative data was analysed using Statistical Package for the Social Sciences (SPSS Version 22) tool to conduct descriptive analysis. The qualitative results obtained from the transcribed focus group interviews in this study revealed the various behavioural patterns of how undergraduate students self-directed their learning. This focus group interview was conducted to reveal the various ways students organised and strategised their learning patterns in order to derive satisfaction in their distinctive learning behaviours and encourage motivation within their study approaches. Quantitative data collected online included a 30 items survey of which 17 respondents completed the survey items in the blended-learning study. The online course survey included 19 items of which data were gathered from 11 respondents.FindingsAcross the data, it is noticeable and clear that time management and goal setting were among the dimensions that are highly rated close to high level among SRL skills investigated in this study. We found that goal setting and task strategies predicted much better attainment of individuals controlling personal course goals, while help seeking was associated with lower goal attainment among majority of the participants.Research limitations/implicationsThe study also identified several challenges. For example, there were some challenges in learners completing the survey questions even when several reminders were sent out forth nightly. At this preliminary stage, learners participated as lurkers without engaging fully with other non-academic and academic interactive activities such as surveys, in course quizzes and forums. Most of the participants in this course said they enrolled to know more about the new trend MOOC, to make friends, to have fun and so on. Although, these are some of their intentions for participating, some of the participants at some points contributed to discussion forums.Practical implicationsOur platform currently allows learners to direct their learning within the course and also allow the choice of content prerequisite in order to recommend resources necessary for their learning. This study indicates the necessity to support SRL skills and directing development of self-determination skills among the participants. This study when applied to a larger sample will demonstrate effective measurement on areas of reliability and validity as results from this small sample has indicated some high SRL skill levels for individual learners within the research.Social implicationsHowever, the success of any e-learning or MOOC platform should consider the following best practices and objectives: the learners' entire learning experience, the strategies used in developing the course content, the planning of the course delivery and the methods of delivery. Therefore, all e-learning platforms should be designed with a primary focus on the way students learn to improve their own learning skills and help them regulate their own independent learning habits. In another related study, the success of any e-learning course implementation should be carefully considered with regards to the course's underlying pedagogy and how learners engage with the content.Originality/valueThere are many e-learning platforms in existence globally, but little has been mentioned about the development of a MOOC platform in general that could allow independent learning and also adequately demonstrating the components and features used in these MOOC designs. This research's implication is to aid instructional designers to apply best practices in the development of an online course. The best approach in designing a good course is to consider the learners and how they could engage with the course resources independently and develop the ability to self-direct their learning. One of the main goals of e-learning platforms is primarily based on developing learning resources that would be suitable for linear course structure as directed by the course developer or instructor.

PurposeThe aims of this study are to examine affective responses of university students when viewing their own predictive learning analytics (PLA) dashboards, and to analyse how those responses are perceived to affect their self-regulated learning behaviour.Design/methodology/approachA total of 42 Northern Irish students were shown their own predicted status of academic achievement on a dashboard. A list of emotions along with definitions was provided and the respondents were instructed to verbalise them during the experience. Post-hoc walk-through conversations with participants further clarified their responses. Content analysis methods were used to categorise response patterns.FindingsThere is a significant variation in ways students respond to the predictions: they were curious and motivated, comforted and sceptical, confused and fearful and not interested and doubting the accuracy of predictions. The authors show that not all PLA-triggered affective states motivate students to act in desirable and productive ways.Research limitations/implicationsThis small-scale exploratory study was conducted in one higher education institution with a relatively small sample of students in one discipline. In addition to the many different categories of students included in the study, specific efforts were made to include “at-risk” students. However, none responded. A larger sample from a multi-disciplinary background that includes those who are categorised as “at-risk” could further enhance the understanding.Practical implicationsThe authors provide mixed evidence for students' openness to learn from predictive learning analytics scores. The implications of our study are not straightforward, except to proceed with caution, valuing benefits while ensuring that students' emotional well-being is protected through a mindful implementation of PLA systems.Social implicationsUnderstanding students' affect responses contributes to the quality of student support in higher education institutions. In the current era on online learning and increasing adaptation to living and learning online, the findings allow for the development of appropriate strategies for implementing affect-aware predictive learning analytics (PLA) systems.Originality/valueThe current study is unique in its research context, and in its examination of immediate affective states experienced by students who viewed their predicted scores, based on their own dynamic learning data, in their home institution. It brings out the complexities involved in implementing student-facing PLA dashboards in higher education institutions.

PurposeThis paper presents a reclassification of markers for mixed reality environments that is also applicable to the use of markers in robot navigation systems and 3D modelling. In the case of Augmented Reality (AR) mixed reality environments, markers are used to integrate computer generated (virtual) objects into a predominantly real world, while in Augmented Virtuality (AV) mixed reality environments, the goal is to integrate real objects into a predominantly virtual (computer generated) world. Apart from AR/AV classifications, mixed reality environments have also been classified by reality; output technology/display devices; immersiveness as well as by visibility of markers.Design/methodology/approachThe approach adopted consists of presenting six existing classifications of mixed reality environments and then extending them to define new categories of abstract, blended, virtual augmented, active and smart markers. This is supported with results/examples taken from the joint Mixed Augmented and Virtual Reality Laboratory (MAVRLAB) of the Ulster University, Belfast, Northern Ireland; the Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy and Santasco SrL, Regio Emilia/Milan, Italy.FindingsExisting classification of markers and mixed reality environments are mainly binary in nature and do not adequately capture the contextual relationship between markers and their use and application. The reclassification of markers into abstract, blended and virtual categories captures the context for simple use and applications while the categories of augmented, active and smart markers captures the relationship for enhanced or more complex use of markers. The new classifications are capable of improving the definitions of existing simple marker and markerless mixed reality environments as well as supporting more complex features within mixed reality environments such as co-location of objects, advanced interactivity, personalised user experience.Research limitations/implicationsIt is thought that applications and devices in mixed reality environments when properly developed and deployed enhances the real environment by making invisible information visible to the user. The current work only marginally covers the use of internet of things (IoT) devices in mixed reality environments as well as potential implications for robot navigation systems and 3D modelling.Practical implicationsThe use of these reclassifications enables researchers, developers and users of mixed reality environments to select and make informed decisions on best tools and environment for their respective application, while conveying information with additional clarity and accuracy. The development and application of more complex markers would contribute in no small measure to attaining greater advancements in extending current knowledge and developing applications to positively impact entertainment, business and health while minimizing costs and maximizing benefits.Originality/valueThe originality of this paper lies in the approach adopted in reclassifying markers. This is supported with results and work carried out at the MAV Reality Laboratory of Ulster University, Belfast–UK, the Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste-Italy and Santasco SrL, Regio Emilia, Milan–Italy. The value of present research lies in the definitions of new categories as well as the discussions of how they improve mixed reality environments and application especially in the health and education sectors.

PurposeThe purpose of this paper is to report on developments and applications of mixed reality cubicles and their impacts on learning in higher education. This paper investigates and presents the cost effective application of augmented reality (AR) as a mixed reality technology via or to mobile devices such as head-mounted devices, smart phones and tablets. Discuss the development of mixed reality applications for mobile (smartphones and tablets) devices leading up to the implementation of a mixed reality cubicle for immersive three dimensional (3D) visualizations.Design/methodology/approachThe approach adopted was to limit the considerations to the application of AR via mobile platforms including head-mounted devices with focus on smartphones and tablets, which contain basic feedback–to-user channels such as speakers and display screens. An AR visualization cubicle was jointly developed and applied by three collaborating institutions. The markers, acting as placeholders acts as identifiable reference points for objects being inserted in the mixed reality world. Hundreds of participants comprising academics and students from seven different countries took part in the studies and gave feedback on impact on their learning experience.FindingsResults from current study show less than 30 percent had used mixed reality environments. This is lower than expected. About 70 percent of participants were first time users of mixed reality technologies. This indicates a relatively low use of mixed reality technologies in education. This is consistent with research findings reported that educational use and research on AR is still not common despite their categorization as emerging technologies with great promise for educational use.Research limitations/implicationsCurrent research has focused mainly on cubicles which provides immersive experience if used with head-mounted devices (goggles and smartphones), that are limited by their display/screen sizes. There are some issues with limited battery lifetime for energy to function, hence the need to use rechargeable batteries. Also, the standard dimension of cubicles does not allow for group visualizations. The current cubicle has limitations associated with complex gestures and movements involving two hands, as one hand are currently needed for holding the mobile phone.Practical implicationsThe use of mixed reality cubicles would allow and enhance information visualization for big data in real time and without restrictions. There is potential to have this extended for use in exploring and studying otherwise inaccessible locations such as sea beds and underground caves. Social implications – Following on from this study further work could be done to developing and application of mixed reality cubicles that would impact businesses, health and entertainment.Originality/valueThe originality of this paper lies in the unique approach used in the study of developments and applications of mixed reality cubicles and their impacts on learning. The diverse composition in nature and location of participants drawn from many countries comprising of both tutors and students adds value to the present study. The value of this research include amongst others, the useful results obtained and scope for developments in the future.

Food authentication and quality checks can be carried out by applying machine learning algorithms on spectral data acquired from miniature spectrometers. This is a very appealing solution as the cost-effectiveness of miniature spectrometers extends the range of consumer electronics available for ordinary citizens in the fight against food fraud, widens the range of their applications and shortens the processing time for any in-situ scenario. In this paper, a study of olive oil purity and quality check feasibility carried out on spectral data acquired from a miniature spectrometer is presented. The aim is to gauge the ability of such a device to differentiate between pure olive oil from ones adulterated with vegetable oils on a relatively large dataset. The paper presents a pipeline encompassing various steps including data pre-processing, dimension reduction, classification, and regression analysis. That is, data collected from miniature spectrometers can be of low quality and exhibit distortions, high dimensionality, and collinearity. Hence, various filtering techniques including wavelets analysis, and normalisation algorithms including multiplicative scatter correction are used for pre-processing. Once the dimensionality is reduced using PCA, classical machine learning classification and regression analysis algorithms are deployed as part of a quality evaluation pipeline. This includes SVM, LDA, KNN, Random Forest and PLS. The obtained results show that very high rates of up to 98% can be achieved. An important consequence is that cost-effective miniature spectrometers augmented with a suitable machine learning component can attain comparable results obtained using non-portable and more expensive spectrometers.

Most universities collect large amounts of students' data to enhance teaching, understand student behaviour, and predict their success. However, such practices raise privacy and ethical issues due to sensitive data harvesting practices. Despite the recognised importance of this topic, few empirical studies address how students perceive the ethical issues related to predictive learning analytics (PLA). To redress this, interview data collected from 42 undergraduate and postgraduate students in a Northern Irish university were thematically analysed. Findings suggest that there are at least three distinct groups of students having varying assumptions about ethics in PLA. They are (1) naïve and trusting, (2) cautious and compromising, and (3) enlightened and demanding, and all of them tend to narrowly focus only on the issue of informed consent. An empirically supported argument for the need for PLA researchers to recognise the within-group variations in student populations and to educate all types of students in issues related to ethics is presented.

Vacuum flat plate (VFP) solar thermal collectors exhibit excellent optical and thermal characteristics due to a combination of wide surface area and high vacuum thermal insulation offering a high performance and architecturally versatile collector with a variety of applications for industrial process heat and building integration. A vacuum flat plate solar collector consists of a solar absorber in a flat vacuum enclosure comprising glass or glass and metal covers sealed around the periphery with an array of support pillars to maintain the separation of the enclosure under atmospheric pressure. The edge seal must be both mechanically strong and hermetic to ensure the durability of the internal vacuum over collector lifetime. This presents several challenges for the fabrication of flat vacuum enclosures. In this study a novel sealing technique is presented using a tin-based alloy, Cerasolzer 217, to create the vacuum seal between two glass panes and an edge separating spacer. The sealing process is undertaken at temperatures ≤250 °C allowing the use of thermally tempered glass panes. The mechanical strength of the edge seal was investigated using a tensometer. It was demonstrated that the bond between glass and edge spacer was sufficiently strong to withstand induced stresses in the edge seal region. The edge seal was leak tested using a conventional Helium mass spectrometer leak detector and was shown to possess leak rates low enough to maintain an adequate vacuum pressure to supress conductive and convective heat transfer in the collector. A finite element method (FEM) is developed and validated against the experimental results and employed to predict the stresses in different regions of the enclosure. It was found that the mechanical strength limits of the seal and glass are higher than the stresses in the edge seal region and on the glass surface, respectively.

This paper presents the activity-based reconfigurable learning and training environment build around a “Virtual Energy Efficient House” (v-EEHouse). It provides an interactive context for cross-disciplinary learning and teaching a wide spectrum of STEM topics related to solar energy, energy efficiency, and Internet of Things (IoT) technology. The target audience includes K-12 and higher education students and faculty, and general public. It can also be employed for the professional training of employees of utility industry and IoT service providers.v-EEHouse enables users to explore energy consumption by major home systems and appliances, get familiar with the IoT technology and the domestic use of renewable energy sources, and adapt an energy-responsible behavior. The v-EEHouse and its individual components can be integrated with online courses including these delivered via the MOOC platforms including edX.Application of the environment in different countries (USA, UK, Ghana, and Tanzania), at diverse educational levels and in various settings, as well as students and instructors’ feedback is discussed.

Online courses in engineering, technology and natural sciences in most parts of the world suffer from the lack of practical hands-on experimentation as an integral part of the curriculum being provided. The use of virtual labs and equipment facilitates active online learning. This meets habits of today's students who are always online and serves to fully engage them in STEM learning. This paper discusses the challenges and prospects of implementing simulation-based adjustable online learning activities, v-labs and comprehensive e-learning environments for teaching subjects, such as energy efficiency, renewable energy sources, thermodynamics, materials science, and some others to diverse cohorts of students from different parts of the world. The virtual labs were integrated with various online courses, including massive open online courses (MOOC) platforms. The use of these tools results in deeper understanding and transferable knowledge and skills for the learners.

This paper presents the use of highly interactive simulation-based virtual equipment, customizable online laboratories, and integrated e-learning environments for STEM education and professional training. The covered subject areas include X-ray equipment and technologies and their applications for investigating crystal structure and microstructure, various biomanufacturing technologies and equipment, energy sources, energy efficiency, responsible energy consumption, and other topics. The activity-centered approach and gamified pedagogy are consistent with the learning habits of millennials. Adaptable and immersive virtual activities facilitate personalized cross-disciplinary learning STEM principles and laws in the realistic contexts familiar to students from their everyday life and workplace experience. Mastering practical skills are combined with studying theoretical knowledge. The described e-learning tools have been used for performing authentic laboratory and workplace tasks online, preparing students and company personnel for conventional hands-on training, lesson demonstrations, performance-based assessment of gained knowledge and skills, and much more. The browser-based applications are mobile-friendly and can run on Windows, iOS and, Android platforms. They can also be incorporated into online courses available on MOOC platforms.

The aim of this paper is to discuss the approach undertaken for a number of years at two different universities, by the use of continuous assessment, to require as well as to encourage student motivation and improve learning throughout the units. The additional aim was to improve attendance that normally leads to better results for the students, which was achieved, at least partially, on the three study units considered in this paper. There is a need also to reduce the “strain” on the students as they approach the period of the majority of multiple assessments, often all at the end of the semester or the year, each of these being critical to the students passing the particular units.

Mixed reality environments as in-betweens of real-world and virtual-reality (VR) environments are created by combining real world objects with computer generated ones. In general, mixed-reality along with VR technology provides innovative ways of showing relationships and connections in the real world, mainly by complimenting real objects with additional information (text, audio and video overlays). In Science Technology and Engineering (STE) disciplines, collaborative learning is about learners working together in teams or groups on structured learning tasks, that typically have a clearly defined goal and are arranged in such a manner that all members of the team are involved. A collaborative approach builds individual and group accountability in each learner as well as one or more soft skills such as communicating with peers, managing resources and the ability to make decisions. This paper presents the use of mixed-reality environments for personalised learning along with two approaches based on message passing paradigms for implementing collaborative learning in mixed-reality environments. The first approach shows the use of a pair of geographically distant mixed-reality environments for remote collaborative learning, while the second approach show multiple (independent) mixed-reality tools synchronised for co-located group work/learning. The statistical analysis of a research study with over 70 respondents from STE disciplines who were exposed to mixed-reality tools developed using mobile technology is also presented and discussed in the context of collaborative work within mixed-reality environments. The contributions includes unique implementations of mixed-reality based collaborative learning environments capable of providing similar experience to that obtained from traditional real-world environments.

This paper presents a novel machine learning prototype to actively assist hearing-impaired people during sleeping hours. The prototype can learn ambient sounds and intelligently decide if they are indicative of dangerous situations such as warning alarms, or if they are merely unimportant background sounds. The application is targeted towards the hearing-impaired who will have removed hearing aids or external components of cochlear implants before sleep. Any sounds of importance can then be translated into vibrations to awaken the sleeping hearing impaired user. The system is suggestive of future smart interactive machines to assist and protect those with either hearing loss or profound deafness.

Smart (ICT based) technologies and applications are increasingly used as teaching/learning aids in various fields of engineering and science capable of supporting both classroom taught courses and hands-on laboratory work as they can potentially encourage creativity and learning in individuals when properly based on adequate learning theories, styles and approaches. This paper presents several smart (mixed reality) technologies and applications for learning in Engineering education and discusses some issues such as knowledge integration and virtual experimentation in the context of applying smart technologies for visualisation in higher science and engineering education along with results from a study carried out at two academic institutions. The contributions of this paper includes a measurable cost-effective use of smart technologies and applications for visualisation based on adequate learning theories, styles and approaches with knowledge integration suitable for engineering disciplines also in developing countries.

E-learning includes elements of both on-line and off-line learning (and/or distance learning). Various Learning and Course Management Systems (LCMS) are used for blended or hybrid learning in Science, Technology and Engineering (STE) disciplines, where they provide a defined (guided) path of study intended for collaborative groups of learners (such as a typical classroom) within the confines of a closed web-based (online) environment. In the blended learning approach, e-learning platforms augment or enhance the face-to-face (traditional) approach to teaching, focusing on the adaptation and delivery of pedagogical material. Key challenges affecting the wider use of e-learning platforms in STE disciplines include lack of adequate support for practical/laboratory work, the need to reformat/transform existing pedagogical content for on-line use, the added demands of on-line interactivity on the part of instructors/providers of content and the accessing them from resource constraint environments. This paper presents two techniques that could be used to reduce the overhead of reformatting or adapting pedagogical material for use as learning objects, as well as, addressing the fundamental challenge of accessing/using online educational resources from resource constrained environments. The results obtained from experimental study are also presented and discussed as potential enhancements for self/personal and group learning.

PurposeThe purpose of this paper is to present an improved concept of software‐based laboratory exercises, namely a Virtual Laboratory for Engineering Sciences (VLES).Design/methodology/approachThe implementation of distance learning and e‐learning in engineering sciences (such as Mechanical and Electrical Engineering) is still far behind current practice in narrative disciplines (Economics, Management, etc.). This is because education in technical disciplines requires laboratory exercises, providing skill‐acquisition and hands‐on experience. In order to overcome this problem for distance‐learning developers and practitioners, a new modular and hierarchically organized approach is needed.FindingsThe concept involves simulation models to emulate system dynamics, full virtual reality to provide visualization, advanced social‐clubbing to ensure proper communication, and an AI tutor to supervise the lab work. Its modularity and hierarchical organization offer the possibility of applying the concept to practically any engineering field: a higher level provides the general framework – it considers lab workplaces as objects regardless of the technical field they come from, and provides communication and supervision – while the lower level deals with particular workplaces. An improved student's motivation is expected.Originality/valueThe proposed concept aims rather high, thus making the work truly challenging. With the current level of information and communication technologies, some of the required features can only be achieved with difficulty; however, the rapid growth of the relevant technologies supports the eventual practicality of the concept. This paper is not intended to present any final results, solutions, or experience. The idea is to promote the concept, identify problems, propose guidelines, and possibly open a discussion.

This book constitutes the refereed proceedings of the 7th International Conference on Computer Supported Education, CSEDU 2015, held in Lisbon, Portugal, in May 2015. The 34 revised full papers presented together with an invited talk were carefully reviewed and selected from 196 submissions. The papers address topics such as information technologies supporting learning; learning/teaching methodologies and assessment; social context and learning environments; domain applications and case studies; and ubiquitous learning.