Analytics for Action: Assessing effectiveness and impact of data informed interventions on online modules

Hidalgo, Rafael; Evans, Gerald E.

doi:10.5944/ried.23.2.26450

Cited by 4 publications

(6 citation statements)

References 10 publications

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“…The initial Analytics4Action project became business as usual after positive reactions by staff. Since 2016 Analytics4Action programme led by the OU Learning Design team has supported over 213 modules, 603 staff and 611 data support meetings in total, impacting learning designs and interventions for around 158.000 students (Hidalgo, 2021;Hidalgo & Evans, 2020). Furthermore, the sharing of learning analytics practices from the OU with other HEIs has resulted in an impact on the understanding, learning and practice of 1541 university educators over a dozen countries, including Belarus (Olney et al, 2020), China (Olney et al, 2021), Kenya (Mittelmeier et al, 2018), and South Africa (Greyling et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…For example, in 2017/18 the learning design team worked with 49 modules, running 136 module data support meetings for a total of 128 teaching staff. As illustrated in the seven selected interventions by Hidalgo and Evans (2020), several showed a positive effect relative to the previous cohort. One way to further strengthen the outcome analysis is to triangulate the quantitative data with the lived experiences of learners.…”

Section: Box 1 Application Of Advanced Learning Analytics With Ou Ana...mentioning

confidence: 94%

“…At the OU teachers often use a combination of scholarly research with critical reflection on lessons-learned using the yearly quality enhancement monitoring to determine whether (or not) a particular intervention strategy has worked or not . For example, within the Analytics4Action approach teachers frequently reflect together with the learning design team whether or not a particular intervention has worked (Hidalgo & Evans, 2020). For example, in 2017/18 the learning design team worked with 49 modules, running 136 module data support meetings for a total of 128 teaching staff.…”

Section: Box 1 Application Of Advanced Learning Analytics With Ou Ana...mentioning

confidence: 99%

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Making sense of learning data at scale

Rienties¹,

Herodotou²

2022

Handbook of Digital Higher Education

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In many higher educational institutions teachers and managers have unprecedented levels of access to data of learners and their learning. In particular during COVID-19 teachers suddenly had to make sense of what their learners were doing away from the classroom. In this chapter we will provide a range of evidence-based guidelines and best-practices based upon implementing online learning and making sense of learning data on a large-scale institutional level. The Open University UK has been implementing learning analytics at scale and has made learning analytics dashboards available to thousands of teachers. How to make sense of these interactive data streams is complex at the best of times, especially in a situation when most teachers are working remotely. We will reflect on our lived experiences of helping teachers to make sense of learning data, and how their voices are essential for senior managers to build powerful data practices.

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Section: Discussionmentioning

confidence: 99%

Section: Box 1 Application Of Advanced Learning Analytics With Ou Ana...mentioning

confidence: 94%

Section: Box 1 Application Of Advanced Learning Analytics With Ou Ana...mentioning

confidence: 99%

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Making sense of learning data at scale

Rienties¹,

Herodotou²

2022

Handbook of Digital Higher Education

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“…The selected studies were screened for the theoretical foundations grounding the use of LA tools for LD improvement. There were papers that showcased the use of the following theoretical frameworks: Analytics for Action framework (Hidalgo & Evans, 2020) T A B L E 3 Methods of data collection in the selected papers. Then, the studies were classified based on the approach that grounded the LA integration into the course design (4 out of 49 were excluded due to disregarding the issue):…”

Section: Rq3mentioning

confidence: 99%

“…nity of Inquiry theoretical framework(Fan et al, 2021;Hidalgo & Evans, 2020). Some of the authors introduced their own frameworks.For instance,Law and Liang (2020) proposed 'A Multilevel Framework and Method for Learning Analytics Integrated Learning Design' for a meaningful integration of learning theory, LA and LD.…”

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confidence: 99%

Learning analytics driven improvements in learning design in higher education: A systematic literature review

Drugova,

Zhuravleva,

Zakharova

et al. 2023

Computer Assisted Learning

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BackgroundDriven by the ongoing need to provide high‐quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear.ObjectivesThis study is aimed to evaluate the maturity of research discussing LA‐driven LD improvements in higher education.MethodsThe systematic review analyses 49 empirical papers, assesses their quality and suggests further research directions. The review elaborates on methodological (research questions, strategy and methods, LA‐LD integration theoretical backgrounds) and substantial (LA‐driven LD improvements, types of data used, LA software development) features of the papers.Results and ConclusionsThe findings demonstrated the lack of theoretical alignment between LA and LD, with research tending towards user experience studies. The most frequently used research strategy was a case study; experiments were very rare. Researchers predominantly used parsing for collecting data and AI methods for analysing it; mostly used data types related to registering learners' engagement with learning activities as well as resources and tools provided in digital learning environments.TakeawaysThe research area discussing LA‐driven LD improvements still has a way to go before attaining the level of full maturity. Only a third of the papers reported actual LA‐driven LD improvements; moreover, only three papers measured their effectiveness. The presented LA software was mostly at the beta or implementation stages and did not assess the impact of using this software.

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