This unit considers the role of technology within learning and the use of technology-enabled content and platforms within organisations. It focuses on how data, learning analytics and artificial intelligence (AI) may be utilised by the learning and development function, while exploring the implementation of technological systems and considering the potential barriers to success.
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Your 7OS03 assignment questions will closely follow these assessment criteria. Here's what the marker is looking for in each one.
Cover the key developments in technology and their application within the learning function — the demand and drivers behind the advance of technology within learning. Discuss learning in the flow of work, bite-sized learning, self-directed learning, simulations, and scalable solutions. Include a critical review of open-source and publicly accessible learning. The marker expects analysis that explains the causes of growth, not just describes the trend. Consider push factors (organisational efficiency, cost reduction) and pull factors (learner expectations, remote working).
Cover the trajectory of technology with respect to learning — LMS/LXP systems, augmented reality (AR) and virtual reality (VR), artificial intelligence, personalisation of learning through technology, smart devices and wearable technology. The marker wants an informed discussion of where technology-enabled learning is heading, grounded in current evidence and trends rather than speculation. Consider both the opportunities and the risks of emerging technologies.
Cover the challenges of measuring ROI for learning technologies — the mismanagement of technology within learning, costs of learning technologies (procurement, implementation, maintenance, training), and methods for calculating return on investment. Discuss how to ensure a positive return from investment in learning technologies. The marker expects you to explain why ROI is complex in this area, not just state that it is important.
Cover three areas: (1) Assessment of learning needs — diagnostic approaches, data and insights from organisational and learning systems (CRM/LMS/LXP). (2) Design and delivery — private and public platforms, learner-generated content, content management systems, LMS/LXP, blended learning design, emerging trends (AR/VR, AI), personalisation. (3) Evaluation — LMS/LXP data, engagement vs completion rates, workplace-based technology to demonstrate learning transfer, and learning analytics. The marker expects analysis that connects technology to improved learning outcomes at each stage.
Cover private content platforms and learning management systems, public and open-source platforms (Google, YouTube, Teams/Zoom), generic, bespoke, and curated learning content, and the use of technological platforms within globally dispersed organisations. The marker expects analysis of how context (organisation size, sector, geography, budget) determines which technological solutions are most appropriate, not a generic tour of available tools.
Cover the role of technology in engaging learners, debates about gamification, the advantages and disadvantages of user-generated content, and using technological systems to encourage collaboration and communities of practice. The marker wants a balanced review — technology can enhance engagement but also create barriers (digital fatigue, exclusion, passive consumption). Discuss the evidence for what actually drives engagement in technology-enabled learning.
Cover definitions and characteristics of effective blended learning, examples of successful blended approaches, and criticisms of blended approaches. The marker expects evaluation — assess what makes blended learning effective (not just convenient), the design principles that underpin good blended learning, and the common pitfalls that undermine it.
Cover data security, security of technological platforms, security policies, methods of protection, and threats from cyber-attacks. The marker expects you to critically discuss the specific security challenges that learning systems face and the practical steps organisations should take to protect both their platforms and the learner data they hold.
Cover operational challenges (resource constraints, technical infrastructure, equity and access issues, stakeholder management), risk aversion, lack of shared vision, resistance to change, and skills gaps among L&D professionals. Discuss methods to mitigate these barriers — building effective business cases, communicating the need for change, encouraging experimentation and innovation, and monitoring engagement. The marker expects a critical discussion that goes beyond listing barriers to analysing why they persist and how they can be overcome.
Cover basic project management methodologies applied to learning technology implementation, operational steps, the use of minimum viable products (MVP) with iterative improvements, pilot testing, human-centred design considerations, and working effectively with suppliers. The marker wants a practical examination of what successful implementation looks like — the process, the people involved, the decisions required, and the common causes of failure.
Cover gathering data to analyse the impact of technology within learning, relevant evaluation models (Kirkpatrick, Brinkerhoff, LTEM, Weinbauer-Heidel, Technology Acceptance Model), learning transfer, and workplace impact. The marker expects evaluation of how organisations can use data to determine whether learning technology implementation has been successful, including the challenges of measuring impact and attributing outcomes to the technology itself.
Cover learning analytics — sources of data, data management, data mining, access and ownership of data, challenges in complex data analysis. Discuss the role of descriptive, inferential, predictive, and prescriptive analytics, and data visualisation. The marker wants examination of both the potential and the practical challenges of learning analytics, including the skills required and the risk of drawing misleading conclusions from incomplete data.
Cover learning management systems (LMS), learning experience platforms (LXP), content management systems (CMS), virtual learning environments (VLE), and the development of learning systems in an evolving technology landscape. The marker expects critical discussion — assess the strengths and limitations of different systems, consider how the market is evolving, and discuss the practical challenges of selecting, implementing, and maintaining learning systems.
Cover the AI landscape including text generators, video and image production, and research tools. Discuss how AI systems can aid L&D, ethical considerations, data protection, chatbots, personalisation of learning, real-time feedback provision, and using AI to scale learning delivery. The marker expects evaluation — weigh up the genuine potential of AI in L&D against the hype, ethical concerns, and practical limitations.
Cover data protection and data integrity, the importance of good quality data, relevant legal regulations (GDPR in the UK/EU), regulations as they apply to data collected by the learning function, access, ownership, transparency, control of data, and preventing data breaches. The marker expects a practical discussion that connects legal requirements to the specific data handling responsibilities of the L&D function.
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