Crafting a rich and personal blending learning environment: an institutional case study from a STEM perspective

Institutional pressures to make optimal use of lecture halls and classrooms can be powerful motivators to identify resources to develop technology enhanced learning approaches to traditional curricula. From the academic’s perspective, engaging students in active learning and reducing the academic workload are important and complementary drivers. This paper presents a case study of a curriculum development exercise undertaken in a STEM subject area at a research-intensive UK university. A multi-skilled team of academics and learning designers have worked collaboratively to build this module which will be realised as a mix of online and face to face activities. Since the module addresses professional issues, a strong emphasis is being placed on establishing authentic learning activities and realistic use of prominent social tools.The learning designers are working for a cross-institutional initiative to support educational innovations; therefore it is important to carefully document the development process and to identify reusable design patterns which can be easily explained to other academics.<br/

Beyond Surveys: Analyzing Software Development Artifacts to Assess Teaching Efforts

This Innovative Practice Full Paper presents an approach of using software development artifacts to gauge student behavior and the effectiveness of changes to curriculum design. There is an ongoing need to adapt university courses to changing requirements and shifts in industry. As an educator it is therefore vital to have access to methods, with which to ascertain the effects of curriculum design changes. In this paper, we present our approach of analyzing software repositories in order to gauge student behavior during project work. We evaluate this approach in a case study of a university undergraduate software development course teaching agile development methodologies. Surveys revealed positive attitudes towards the course and the change of employed development methodology from Scrum to Kanban. However, surveys were not usable to ascertain the degree to which students had adapted their workflows and whether they had done so in accordance with course goals. Therefore, we analyzed students' software repository data, which represents information that can be collected by educators to reveal insights into learning successes and detailed student behavior. We analyze the software repositories created during the last five courses, and evaluate differences in workflows between Kanban and Scrum usage

Models of everywhere revisited: a technological perspective

The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and nonlinearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment

Virtual learning process environment (VLPE): a BPM-based learning process management architecture

E-learning systems have significantly impacted the way that learning takes place within universities, particularly in providing self-learning support and flexibility of course delivery. Virtual Learning Environments help facilitate the management of educational courses for students, in particular by assisting course designers and thriving in the management of the learning itself. Current literature has shown that pedagogical modelling and learning process management facilitation are inadequate. In particular, quantitative information on the process of learning that is needed to perform real time or reflective monitoring and statistical analysis of students’ learning processes performance is deficient. Therefore, for a course designer, pedagogical evaluation and reform decisions can be difficult. This thesis presents an alternative e-learning systems architecture - Virtual Learning Process Environment (VLPE) - that uses the Business Process Management (BPM) conceptual framework to design an architecture that addresses the critical quantitative learning process information gaps associated with the conventional VLE frameworks. Within VLPE, course designers can model desired education pedagogies in the form of learning process workflows using an intuitive graphical flow diagram user-interface. Automated agents associated with BPM frameworks are employed to capture quantitative learning information from the learning process workflow. Consequently, course designers are able to monitor, analyse and re-evaluate in real time the effectiveness of their chosen pedagogy using live interactive learning process dashboards. Once a course delivery is complete the collated quantitative information can also be used to make major revisions to pedagogy design for the next iteration of the course. An additional contribution of this work is that this new architecture facilitates individual students in monitoring and analysing their own learning performances in comparison to their peers in a real time anonymous manner through a personal analytics learning process dashboard. A case scenario of the quantitative statistical analysis of a cohort of learners (10 participants in size) is presented. The analytical results of their learning processes, performances and progressions on a short Mathematics course over a five-week period are also presented in order to demonstrate that the proposed framework can significantly help to advance learning analytics and the visualisation of real time learning data

TRE-FX:Delivering a federated network of trusted research environments to enable safe data analytics

Trusted Research Environments (TREs) are secure locations in which data are placed for researchers to analyse. TREs host administrative data, hospital data or any other data that needs to remain securely isolated, but it is hard for a researcher to perform an analysis across multiple TREs, requesting and gathering the outputs from each one. This is a common problem in the UK's devolved healthcare system of geographical and governance boundaries. There are different ways of implementing TREs and the analysis tools that use them. A solution must be straightforward for existing, independent systems to adopt, must cope with the variety of system implementations, and must work within the "Five Safes" framework that enables data services to provide safe research access to data. TRE-FX assembled leading infrastructure researchers, analysis tool makers, TRE providers and public engagement specialists to streamline the exchange of data requests and results. The "Five Safes RO-Crate" standard packages up (Crates) the Objects needed for Research requests and results with the information needed for the tools and TRE providers to ensure that the crates are reviewed and processed according to Five Safes principles. TRE-FX showed how this works using software components and an end-to-end demonstrator implemented by a TRE in Wales. Two other TREs, in Scotland and England, are preparing to follow suit. Two analysis tool providers (Bitfount and DataSHIELD) modified their systems to use the RO-Crates. The next step is practical implementation as part of the HDR UK programme. Two large European projects will develop the approach further. TRE-FX shows that it is possible to streamline how analysis tools access multiple TREs while enabling the TREs to ensure that the access is safe. The approach scales as more TREs are added and can be adopted by established systems. Researchers will then be able to perform an analysis across multiple TREs much more easily, widening the scope of their research and making more effective use of the UK's data. If we had had this for COVID-19 data analysis, it would have super-charged researchers to be able to quickly answer pressing questions across the UK. This work was funded by UK Research &amp; Innovation [Grant Number MC_PC_23007] as part of Phase 1 of the DARE UK (Data and Analytics Research Environments UK) programme, delivered in partnership with Health Data Research UK (HDR UK) and Administrative Data Research UK (ADR UK)

A Smart Products Lifecycle Management (sPLM) Framework - Modeling for Conceptualization, Interoperability, and Modularity

Autonomy and intelligence have been built into many of today’s mechatronic products, taking advantage of low-cost sensors and advanced data analytics technologies. Design of product intelligence (enabled by analytics capabilities) is no longer a trivial or additional option for the product development. The objective of this research is aimed at addressing the challenges raised by the new data-driven design paradigm for smart products development, in which the product itself and the smartness require to be carefully co-constructed. A smart product can be seen as specific compositions and configurations of its physical components to form the body, its analytics models to implement the intelligence, evolving along its lifecycle stages. Based on this view, the contribution of this research is to expand the “Product Lifecycle Management (PLM)” concept traditionally for physical products to data-based products. As a result, a Smart Products Lifecycle Management (sPLM) framework is conceptualized based on a high-dimensional Smart Product Hypercube (sPH) representation and decomposition. First, the sPLM addresses the interoperability issues by developing a Smart Component data model to uniformly represent and compose physical component models created by engineers and analytics models created by data scientists. Second, the sPLM implements an NPD3 process model that incorporates formal data analytics process into the new product development (NPD) process model, in order to support the transdisciplinary information flows and team interactions between engineers and data scientists. Third, the sPLM addresses the issues related to product definition, modular design, product configuration, and lifecycle management of analytics models, by adapting the theoretical frameworks and methods for traditional product design and development. An sPLM proof-of-concept platform had been implemented for validation of the concepts and methodologies developed throughout the research work. The sPLM platform provides a shared data repository to manage the product-, process-, and configuration-related knowledge for smart products development. It also provides a collaborative environment to facilitate transdisciplinary collaboration between product engineers and data scientists