Short presentation given at the 'Building Open Science and Scholarship in SoLAR' workshop at LAK22, in March 2022. It touches on aspects of open scholarship including open access, open peer review, open thinking, open research teams, open research methods and an open research environment.

1. 1
Qualitative Perspectives
on Open Science
Rebecca Ferguson
The Open University, UK
Building Open Science and Scholarship in SoLAR
Workshop at LAK22

2. 2
What is open science?
Open science aims to bolster scientific research in part by testing the
reproducibility and replicability of findings. (APA)
Open science encompasses unhindered access to scientific articles, access
to data from public research, and collaborative research (OECD)
An approach to the scientific process that focuses on spreading knowledge
as soon as it is available using digital and collaborative technology. (EC)
Usage of the term varies substantially across disciplines (Wikipedia)
As Tennant et al. (2020) note, the term open science “implicitly seems only
to regard ‘scientific’ disciplines, whereas open scholarship can be
considered to include research from the Arts and Humanities” (Wikipedia)
Tennant et al, Foundations for Open Scholarship Strategy Development https://osf.io/preprints/metaarxiv/b4v8p/
Image from IOSPress

3. 3
Opening up the scientific method
Hypothesis
Experiment
Image from Wikimedia Commons

4. 4
Is it trustworthy?
Is it reliable, valid and generalisable? Is it ethical?

5. 5
A qualitative approach
The question is not whether you are using a mixture of
numerical and non-numerical data, but how that data is
being viewed.
Within a qualitative methodology both numerical and non-
numerical data are viewed in the same way; all data is a
symbolic representation, which needs to be interpreted and
thus its meaning is subjective and context dependent.
Twining et al, Some Guidance on Conducting and Reporting Qualitative Studies http://oro.open.ac.uk/48027/

6. 6
A qualitative approach in LA (1)
RQ1: What are the individual perceptions of 20
educational managers within a distance learning HE
institution about the adoption of predictive learning
analytics in the organisation?
RQ2: What are the challenges that may inhibit wider
adoption of PLA across the institution?
We need more
information to know how
and when to use it best
The tools need to be able to
sell themselves
The tools need to be able to
sell themselves
Using it on a voluntary basis does
not work... we need to be clear on
how much easier we can make
life for teachers with it
Herodotou, Rienties et al, Predictive analytics ‘at scale’, http://oro.open.ac.uk/58991/

7. 7
A qualitative approach in LA (2)
Initial needs analysis and concept generation, including design activities such as
generative card sorting exercises, directed storytelling, semi-structured interviews
with teachers, and field observations
Initial concept validation via speed dating sessions with teachers
Iterative lower-fidelity prototyping, gradually increasing the fidelity of both
prototypes and simulated use contexts, using methods such as role-playing and
bodystorming exercises, participatory sketching and comicboarding, and behavioral
mapping
Iterative higher-fidelity prototyping with replay-based simulation exercises, using
Replay Enactments
Iterative classroom piloting and experimental evaluation, using field
observations, pre-post assessments of student learning, semi-structured interviews
with teachers and students, and behavioral mapping.
Holstein et al, Co-designing a real-time classroom orchestration tool, https://doi.org/10.18608/jla.2019.62.3 l

8. 8
Is it trustworthy?
Is it confirmable, credible, dependable, plausible, and transferable? Is it ethical?
Confirmable: results are confirmed or corroborated by others
Credible: clarity and transparency in the line of reasoning of the
researcher, and authenticity of the interpretation, confirmed by the
researcher or by checking with the subjects themselves.
Dependable: the research accounts for the context in which it takes
place
Plausible: the weight of evidence shown in the density of connections
between the details of the data, and the persuasiveness of the
description of the researcher’s engagement with that data.
Transferable: the research can be generalised or transferred to other
contexts or settings.

9. 9
Open scholarship might include
Open access: anyone can access the findings, even without access to an
academic library
Open peer review: No more ‘Reviewer 2’. Reviewers are named and
discussion is open.
Open thinking: Sharing of initial ideas and mistakes.
Open research teams: Active moves to involve people in the research,
as in citizen science.
Open research methods: such as action research and design-based
research.
Open research environment: transparent and collaborative.
Making all stages of the research journey open and resuable, now and in
the future
Photo by Alex Knight on Unsplash