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Wired magazine’s ‘The Explainer’; VC designate of the OU; and international distance learning expert headline speakers at Association for Learning Technology’s annual conference, starts 8th September
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The learning technologies of the future: technologies that learn?
Get PDFHigher Education Institutions (HEIs) operate in a borderless and complex environment, abundant in potentially useful information. The Creating Academic Learning Futures (CALF) research project, carried out in partnership by the University of Leicester and University College Falmouth in the UK, involves the development of approaches and tools for structuring and filtering information, in order to facilitate institutional decision-making in participative and creative ways. One of the aims of the CALF project is to involve students in creating and exploring a variety of plausible ‘alternative futures’ for learning and teaching technologies in higher education. This paper discusses some of the issues that are emerging in the course of the research process and presents ideas for the future, grounded in and emergent from ‘student voices’ from the CALF research project. Students expected the technologies of the near future to enable them to become co-creators in their own education processes. The future scenarios imagined the rise of learning technologies which instead of becoming outdated with use, become more valuable as more user-generated content is invested, technologies which are truly learning in that they learn about their users and constantly morph/adapt to their users’ needs. Finally, increasing virtualisation was a recurrent theme across most student-generated scenarios. The paper concludes with a discussion of some of the strengths and limitations of using technologies for involving students in creative activities for generating future scenarios for higher education. The technologies used by the project enabled collaborative creative thinking across a broader spectrum of possibilities about the relationship between the present and the future of higher education
Between analysis and transformation: technology, methodology and evaluation on the SPLICE project
Get PDFThis paper concerns the ways in which technological change may entail methodological development in e-learning research. The focus of our argument centres on the subject of evaluation in e-learning and how technology can contribute to consensus-building on the value of project outcomes, and the identification of mechanisms behind those outcomes. We argue that a critical approach to the methodology of evaluation which harnesses technology in this way is vital to agile and effective policy and strategy-making in institutions as the challenges of transformation in a rapidly changing educational and technological environment are grappled with. With its focus on mechanisms and multiple stakeholder perspectives, we identify Pawson and Tilley’s ‘Realistic Evaluation’ as an appropriate methodological approach for this purpose, and we report on its use within a JISC-funded project on social software, SPLICE (Social Practices, Learning and Interoperability in Connected Environments). The project created new tools to assist the identification of mechanisms responsible for change to personal and institutional technological practice. These tools included collaborative mind-mapping and focused questioning, and tools for the animated modelling of complex mechanisms. By using these tools, large numbers of project stakeholders could engage in a process where they were encouraged to articulate and share their theories and ideas as to why project outcomes occurred. Using the technology, this process led towards the identification and agreement of common mechanisms which had explanatory power for all stakeholders. In conclusion, we argue that SPLICE has shown the potential of technologically-mediated Realistic Evaluation. Given the technologies we now have, a methodology based on the mass cumulation of stakeholder theories and ideas about mechanisms is feasible. Furthermore, the summative outcomes of such a process are rich in explanatory and predictive power, and therefore useful to the immediate and strategic problems of the sector. Finally, we argue that as well as generating better explanations for phenomena, the evaluation process can itself become transformative for stakeholders
Sharing lessons through effective modelling
No full textDiscusses why one might want to model and forms of modelling together with a worked example of induction
A comparative analysis of the effects of instructional design factors on student success in e-learning: multiple-regression versus neural networks
Get PDFThis study explores the relationship between the student performance and instructional design. The research was conducted at the E-Learning School at a university in Turkey. A list of design factors that had potential influence on student success was created through a review of the literature and interviews with relevant experts. From this, the five most import design factors were chosen. The experts scored 25 university courses on the extent to which they demonstrated the chosen design factors. Multiple regression and supervised artificial neural network (ANN) models were used to examine the relationship between student grade point averages and the scores on the five design factors. The results indicated that there is no statistical difference between the two models. Both models identified the use of examples and applications as the most influential factor. The ANN model provided more information and was used to predict the course-specific factor values required for a desired level of success
A systemic framework for managing e-learning adoption in campus universities: individual strategies in context
Get PDFThere are hopes that new learning technologies will help to transform university learning and teaching into a more engaging experience for twenty-first-century students. But since 2000 the changes in campus university teaching have been more limited than expected. I have drawn on ideas from organisational change management research to investigate why this is happening in one particular campus university context. My study examines the strategies of individual lecturers for adopting e-learning within their disciplinary, departmental and university work environments to develop a conceptual framework for analysing university learning and teaching as a complex adaptive system. This conceptual framework links the processes through which university teaching changes, the resulting forms of learning activity and the learning technologies used – all within the organisational context of the university. The framework suggests that systemic transformation of a university’s learning and teaching requires coordinated change across activities that have traditionally been managed separately in campus universities. Without such coordination, established ways of organising learning and teaching will reassert themselves, as support staff and lecturers seek to optimise their own work locally. The conceptual framework could inform strategies for realising the full benefits of new learning technologies in other campus universities
