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Date |
2016-12-21 |
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Is Part Of |
repository |
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abstract |
We are pleased to offer you our first Scholarly insight 2016: a Data wrangler perspective.
The OU is going through several fundamental changes, whereby strategic, pedagogical
informed research and insight what drives student learning and academic performance
is essential. Making sense of Big Data in particular can be a challenge, especially
when data is stored at different data warehouses and require advanced statistical
skills to interpret complex patterns of data. In 2012 the Open University UK (OU)
instigated a Data Wrangling initiative, which provided every Faculty with a dedicated
academic with expertise in data analysis and whose task is to provide strategic, pedagogical,
and sense-making advice to staff and senior management. Given substantial changes
within the OU over the last 18 months (e.g., new Faculty structure, real-time dashboards,
increased reliance on analytics), an extensive discussion with various stakeholders
within the Faculties was initiated to make sure that data wranglers provide effective
pedagogical insight based upon best practice and evidence-based analyses and research
(see new Data wrangler structure).
Demand for actionable insights to help support OU staff and senior management in particular
with module and qualification design is currently strong (Miller & Mork, 2013), especially
a desire for evidence of impact of “what works” (Ferguson, Brasher, et al., 2016).
Learning analytics are now increasingly taken into consideration when designing, writing
and revising modules, and in the evaluation of specific teaching approaches and technologies
(Rienties, Boroowa, et al., 2016). A range of data interrogation and visualization
tools developed by the OU supports this (Calvert, 2014; Toetenel & Rienties, 2016b).
With the new ways of working with Data Wrangling, first we have provided our basic
statistical analyses in form of our Key Metrics report. Second, from January 2017
onwards we will focus again on dealing with bespoke requests from Faculties, and where
possible share the insights across all Schools and Faculties. Third, this Scholarly
insight has a different purpose to previous Data wrangler work, namely we aim to provide
state-of-the-art and forward looking insights into what drives our students and staff
in terms of learning and learning success. Based upon consultation with the Faculties,
seven key cross-Faculty themes were identified that influence our students’ learning
experiences, academic performance, and retention. The first five chapters focus on
how the OU designs modules, formative and summative assessments and feedback, helps
students from informal to formal learning, and how these learning designs influence
student satisfaction. All five chapters indicate that the way we design our modules
fundamentally influences student satisfaction, and perhaps more importantly academic
retention. Clear guidelines and good-reads are provided for how module teams, ALs,
and others can improve our focus on Students First. In Chapter 6-7, we specifically
address how individual student demographics (e.g., age, ethnicity, prior education)
and accessibility in particular influence the students’ learning journeys, with concrete
suggestions how to support our diverse groups of students. Note that each chapter
can be read independently and in any particular order. We are looking forward to your
feedback. |
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authorList |
authors |
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status |
peerReviewed |
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uri |
http://data.open.ac.uk/oro/document/557838 |
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uri |
http://data.open.ac.uk/oro/document/557839 |
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uri |
http://data.open.ac.uk/oro/document/557840 |
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uri |
http://data.open.ac.uk/oro/document/557841 |
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uri |
http://data.open.ac.uk/oro/document/557842 |
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uri |
http://data.open.ac.uk/oro/document/557843 |
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uri |
http://data.open.ac.uk/oro/document/566413 |
| 48244 |
type |
Article |
| 48244 |
label |
Rienties, Bart ; Edwards, Chris ; Gaved, Mark ; Marsh, Vicky ; Herodotou, Christothea
; Clow, Doug ; Cross, Simon ; Coughlan, Tim ; Jones, Jan and Ullmann, Thomas (2016).
Scholarly insight 2016: a Data wrangler perspective. Open University UK. |
| 48244 |
label |
Rienties, Bart ; Edwards, Chris ; Gaved, Mark ; Marsh, Vicky ; Herodotou, Christothea
; Clow, Doug ; Cross, Simon ; Coughlan, Tim ; Jones, Jan and Ullmann, Thomas (2016).
Scholarly insight 2016: a Data wrangler perspective. Open University UK. |
| 48244 |
Publisher |
ext-f671d04ff80fb756a98e1b8bdacfe6bf |
| 48244 |
Title |
Scholarly insight 2016: a Data wrangler perspective |
| 48244 |
in dataset |
oro |