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The following publication contains book reviews of these titles: Bearman, M., Dawson, P., Ajjawi, R., Tai, J., Boud, D. (eds.) (2020) Re-imagining university assessment in a digital world. The Enabling Power of Assessment 7. Springer, 296 pages, https://doi.org/10.1007/978-3-030-41956-1_2 Yu, S., Ally, M., Tsinakos, A. (eds) (2020) Emerging technologies and pedagogies in the curriculum. London: Routledge, 463 pages, ISBN 978-981-15-0618-5 Morgana, V., & Kukulska-Hulme, A. (eds.) (2021) Mobile assisted language learning across educational contexts. Routledge, 152 pages, ISBN: 9780367521745 Holmes, W., Bialik, M., Fadel, C. (2019) Artificial Intelligence in education: Promises and implications for teaching and learning. Boston, MA: Center for Curriculum Redesign, 228 pages, ISBN 1-79429-370-1; 978-1-79429-370-0
Sarsfield M, 2021, Short and fat or long and thin: the educational impact of the shape of the timetable, Association for Learning Technology Conference 2021
The COVID pandemic led to many changes in educational practice during the academic year 2020-21. Most of the teaching, learning and assessment took place online rather than in person and some institutions made changes to the structure of their timetable to provide greater flexibility in delivery (e.g. Nerantzi and Chatzidamianos, 2020). In some practical programmes, delivery was rearranged, so theoretical content was delivered online in the initial months of the pandemic with hands-on activities rescheduled for later in the year. The changes often involved rearranging content from a number of long, thin blocks, taught concurrently over a semester, into consecutive short, fat blocks, with content on one topic being delivered intensively over a short period, followed by further blocks covering different topics.As a result of these experiences, some departments and teaching staff are reconsidering how their programmes will be delivered in the future, e.g. considering more online delivery and restructuring of timetables, potentially with increased adoption of teaching in short, fat blocks (also known as block, accelerated or intensive delivery).This session will explore issues around delivery in traditional (long, thin) and intensive (short, fat) mode in on-campus and online programmes, drawing on research findings from large-scale quantitative studies such as Loton et al. (2020), who studied the impact on student performance (n=86,545) and satisfaction (n=15,989) after a university-wide move to block delivery, and in-depth qualitative studies such as Lee & Horsfall (2010), who reported on student (n=114) and staff (n=12) experiences on traditionally and intensively delivered modules, using survey and interview data respectively.A change in delivery mode can have significant impacts on approaches to teaching, learning and assessment (Walsh, Sanders & Gadgil, 2019; Dixon & O’Gorman, 2020). Attendees will be prompted to discuss the implications of the sh
Sarsfield M, Conway J, 2018, What can we learn from learning analytics? A case study based on an analysis of student use of video recordings, Research in Learning Technology, Vol: 26, ISSN: 2156-7069
Over recent years the use of lecture capture technology has become widespread in higher education. However, clear evidence of the learning benefits of this technology is limited, with contradictory findings reported in the literature. The reasons for this lack of consistent evidence may include methodological issues and differences in the context of previous studies. This paper describes a study using server log data to explore student use of video recordings quantitatively in the context of science courses at Imperial College London. The study had two aims: to understand more about the general principles that underpin a learning analytics study and to seek answers to the following specific research questions: (1) How much use is made of video recordings? (2) How does the use of recordings in a module vary over time? (3) Is the use of recordings different for different modules/subjects? (4) Is the use of recordings different for subgroups of students, e.g. students with specific learning differences or English as a second language, students attaining different grades? (5) Is the use of recordings different for different types of content? Using learning analytics enabled the discovery of context-specific actionable insights: recommendations for both staff and students and ideas for further research. General conclusions were also drawn on how best to undertake learning analytics studies in order to deliver evidence and insights to improve learning and teaching.
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