To Opt in or to Opt Out? Predicting Student Preference for Learning Analytics-Based Formative Feedback
Teachers’ work is increasingly augmented with intelligent tools that extend their pedagogical abilities. While these tools may have positive effects, they require use of students’ personal data, and more research into student preferences regarding these tools is needed. In this...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9893791/ |
| _version_ | 1811264745150349312 |
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| author | Joonas Merikko Kwok Ng Mohammed Saqr Petri Ihantola |
| author_facet | Joonas Merikko Kwok Ng Mohammed Saqr Petri Ihantola |
| author_sort | Joonas Merikko |
| collection | DOAJ |
| description | Teachers’ work is increasingly augmented with intelligent tools that extend their pedagogical abilities. While these tools may have positive effects, they require use of students’ personal data, and more research into student preferences regarding these tools is needed. In this study, we investigated how learning strategies and study engagement are related to students’ willingness to share data with learning analytics (LA) applications and whether these factors predict students’ opt-in for LA-based formative feedback. Students (N = 158) on a self-paced online course set their personal completion goals for the course and chose to opt in for or opt out of personalized feedback based on their progress toward their goal. We collected self-reported measures regarding learning strategies, study engagement, and willingness to share data for learning analytics through a survey (N = 73). Using a regularized partial correlation network, we found that although willingness to share data was weakly connected to different aspects of learning strategies and study engagement, students with lower self-efficacy were more hesitant to share data about their performance. Furthermore, we could not sufficiently predict students’ opt-in decisions based on their learning strategies, study engagement, or willingness to share data using logistic regression. Our findings underline the privacy paradox in online privacy behavior: theoretical unwillingness to share personal data does not necessarily lead to opting out of interventions that require the disclosure of personal data. Future research should look into why students opt in for or opt out of learning analytics interventions. |
| first_indexed | 2024-04-12T20:09:54Z |
| format | Article |
| id | doaj.art-22029661280641ee9d393c147aa114b1 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T20:09:54Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-22029661280641ee9d393c147aa114b12022-12-22T03:18:17ZengIEEEIEEE Access2169-35362022-01-0110991959920410.1109/ACCESS.2022.32072749893791To Opt in or to Opt Out? Predicting Student Preference for Learning Analytics-Based Formative FeedbackJoonas Merikko0https://orcid.org/0000-0003-4166-4762Kwok Ng1Mohammed Saqr2https://orcid.org/0000-0001-5881-3109Petri Ihantola3https://orcid.org/0000-0003-1197-7266Department of Education, Faculty of Educational Sciences, University of Helsinki, Helsinki, FinlandPhilosophical Faculty, School of Educational Sciences and Psychology, University of Eastern Finland, Joensuu, FinlandFaculty of Science and Forestry, School of Computing, University of Eastern Finland, Joensuu, FinlandDepartment of Education, Faculty of Educational Sciences, University of Helsinki, Helsinki, FinlandTeachers’ work is increasingly augmented with intelligent tools that extend their pedagogical abilities. While these tools may have positive effects, they require use of students’ personal data, and more research into student preferences regarding these tools is needed. In this study, we investigated how learning strategies and study engagement are related to students’ willingness to share data with learning analytics (LA) applications and whether these factors predict students’ opt-in for LA-based formative feedback. Students (N = 158) on a self-paced online course set their personal completion goals for the course and chose to opt in for or opt out of personalized feedback based on their progress toward their goal. We collected self-reported measures regarding learning strategies, study engagement, and willingness to share data for learning analytics through a survey (N = 73). Using a regularized partial correlation network, we found that although willingness to share data was weakly connected to different aspects of learning strategies and study engagement, students with lower self-efficacy were more hesitant to share data about their performance. Furthermore, we could not sufficiently predict students’ opt-in decisions based on their learning strategies, study engagement, or willingness to share data using logistic regression. Our findings underline the privacy paradox in online privacy behavior: theoretical unwillingness to share personal data does not necessarily lead to opting out of interventions that require the disclosure of personal data. Future research should look into why students opt in for or opt out of learning analytics interventions.https://ieeexplore.ieee.org/document/9893791/Feedbacklearning strategiesopt-inprivacyself-regulationstudy engagement |
| spellingShingle | Joonas Merikko Kwok Ng Mohammed Saqr Petri Ihantola To Opt in or to Opt Out? Predicting Student Preference for Learning Analytics-Based Formative Feedback IEEE Access Feedback learning strategies opt-in privacy self-regulation study engagement |
| title | To Opt in or to Opt Out? Predicting Student Preference for Learning Analytics-Based Formative Feedback |
| title_full | To Opt in or to Opt Out? Predicting Student Preference for Learning Analytics-Based Formative Feedback |
| title_fullStr | To Opt in or to Opt Out? Predicting Student Preference for Learning Analytics-Based Formative Feedback |
| title_full_unstemmed | To Opt in or to Opt Out? Predicting Student Preference for Learning Analytics-Based Formative Feedback |
| title_short | To Opt in or to Opt Out? Predicting Student Preference for Learning Analytics-Based Formative Feedback |
| title_sort | to opt in or to opt out predicting student preference for learning analytics based formative feedback |
| topic | Feedback learning strategies opt-in privacy self-regulation study engagement |
| url | https://ieeexplore.ieee.org/document/9893791/ |
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