eprintid: 10142097
rev_number: 12
eprint_status: archive
userid: 608
dir: disk0/10/14/20/97
datestamp: 2022-02-02 17:01:53
lastmod: 2022-02-02 17:01:53
status_changed: 2022-02-02 17:01:53
type: book_section
metadata_visibility: show
creators_name: Korir, M
creators_name: Slade, S
creators_name: Holmes, W
creators_name: Rienties, B
title: Eliciting students' preferences for the use of their data for learning analytics. A crowdsourcing approach.
ispublished: pub
divisions: UCL
divisions: B16
divisions: B14
divisions: J77
note: The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.
abstract: Research on student perspectives of learning analytics suggests that students are generally unaware of the collection and use of their data by their learning institutions, and they are often not involved in decisions about whether and how their data are used. To determine the influence of risks and benefits awareness on students’ data use preferences for learning analytics, we designed two interventions: one describing the possible privacy risks of data use for learning analytics and the second describing the possible benefits. These interventions were distributed amongst 447 participants recruited using a crowdsourcing platform. Participants were randomly assigned to one of three experimental groups – risks, benefits, and risks and benefits – and received the corresponding intervention(s). Participants in the control group received a learning analytics dashboard (as did participants in the experimental conditions). Participants’ indicated the motivation for their data use preferences. Chapter 11 will discuss the implications of our findings in relation to how to better support learning institutions in being more transparent with students about the practice of learning analytics.
date: 2022-01-26
date_type: published
publisher: Routledge
official_url: https://www.taylorfrancis.com/chapters/oa-edit/10.4324/9781003177098-13/eliciting-students-preferences-use-data-learning-analytics-maina-korir-sharon-slade-wayne-holmes-bart-rienties
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1915492
doi: 10.4324/9781003177098
isbn_13: 9781003177098
lyricists_name: Holmes, Wayne
lyricists_id: WHOLM20
actors_name: Holmes, Wayne
actors_id: WHOLM20
actors_role: owner
full_text_status: public
place_of_pub: Abingdon, UK
pagerange: 144-156
book_title: Open World Learning. Research, Innovation and the Challenges of High-Quality Education.
edition: 1st
editors_name: Rienties, B
editors_name: Hampel, R
editors_name: Scanlon, E
citation:        Korir, M;    Slade, S;    Holmes, W;    Rienties, B;      (2022)    Eliciting students' preferences for the use of their data for learning analytics. A crowdsourcing approach.                    In: Rienties, B and Hampel, R and Scanlon, E, (eds.) Open World Learning. Research, Innovation and the Challenges of High-Quality Education. (pp. 144-156).   Routledge: Abingdon, UK.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10142097/1/Korir%20et%20al.pdf