(1) The purpose of this Policy is to: (2) The use of learning analytics at UOW forms part of the broader activities undertaken to support students through their studies and reach their full academic potential. (3) This Policy applies to any person responsible for the preparation, analysis, decisions and actions at UOW arising directly from learning analytics. (4) The data sources used for learning analytics at UOW cover the key aspects of the UOW learning platform. This includes, but is not limited: (5) Data related to student utilisation of counselling services is protected by health records privacy legislation and excluded from use in learning analytics. (6) While the focus of learning analytics at UOW is on near real-time delivery of learning related information to our staff and students to support the student learning experience, the scope of this Policy includes the continuous improvement of teaching and learning. This includes academic or professional services staff engaged in research activities associated with the University. (7) The scope of this Policy includes all related activities within the information management lifecycle of learning analytics data as follows: (8) The primary focus of learning analytics is for onshore UOW students. (9) The overarching principles of this Policy are based on a literature review of the ethical and legal issues associated with learning analytics. (10) The University is committed to operating the learning analytics initiatives in a manner, as open and transparent as possible. (11) Duty of care obligations for students requires the University to use learning analytics to monitor student progress towards learning goals. A student is unable to opt-out of inclusion in learning analytics initiatives at the University because of this duty of care obligation. (12) All students must be made aware of learning analytics activities at the University through multiple touch-points, including but not limited to: (13) The data sources, the purposes of the analytics, the metrics used, who has access to the analytics, the boundaries around usage, and how to interpret the data must be explained clearly to staff and students using the touch-points outlined in clause 12. (14) The University must clearly describe the processes involved in producing the analytics to students and staff. This will be done using different channels such as the touch-points outlined in clause 12. (15) Student access to learning analytics is under the following conditions: (16) Students have a right to be able to correct inaccurate personal data held about themselves. (17) The use of learning analytics data at UOW is underpinned by a Privacy Impact Assessment (PIA) undertaken in accordance with the best practice available in higher education sectors worldwide. (18) Access to student data and analytics is restricted to those staff identified by the institution as having a legitimate need to view the data. This includes, but is not limited to the following: (19) Access to the data contained within the learning analytics data warehouse must be managed to protect student privacy: (20) Staff requesting access to the Learning Analytics data warehouse must also have the approval for access to the DASH student information and student equity sensitive data. This serves as a co-requisite with requirements outlined above in clause 19. (21) All applications for access to the learning analytics data warehouse must include: (22) Access to the learning analytics data warehouse will only be provided for purposes allowed within ethical and legal constraints, with evidence of any required approvals. (23) The conditions required for information to be disclosed outside UOW are outlined in the ‘Disclosure of Information’ section of the Privacy Policy. (24) Use of learning analytics data for academic promotion purposes must not contain personally identifiable student information. (25) In order to develop and maintain confidence in learning analytics and ensure it is used to the benefit of students, the University will monitor the quality, robustness and validity of the learning analytics data and processes. (26) The University will take measures to ensure that: (27) All algorithms and metrics used for predictive analytics or interventions will be understood, validated, reviewed and improved by appropriately qualified staff. (28) The circumstances when analytics suggest that a student could benefit from additional support, along with the type and nature of interventions, are specified in the Guidelines for Actioning Learning Analytics Insights. (29) The University will record predictions and interventions made based on insights generated through learning analytics processes. This information will be auditable so the appropriateness and effectiveness of both predications and interventions is available for review. (30) The University recognises that analytics cannot give a complete picture of an individual’s learning. The University is thus required to take into account personal circumstances when deciding the actions to take on insights generated through learning analytics. (31) Opportunities for students to unethically influence the learning analytics will be minimised. This includes preventative actions such as rigorous designs in the source transactional systems. It also includes contingent actions such as robust auditing and careful interpretation of the data. (32) Data analysis focussed on the continuous improvement of teaching and learning activities is undertaken with the support of the DVCA. This support is contingent upon the results of such data analysis not being published, unless express permission has been granted by UOW as per the elements outlined in section 11. (33) Research conducted by the University using learning analytics data is subject to existing research policies at the University. (34) The approval process is covered in Appendix A: Approval Process – University Research Using Analytics Data and includes: (35) The University views any breach of this Policy as extremely serious. Depending on the severity of the breach, a staff member or student may face disciplinary action in accordance with the Academic Misconduct (Coursework) Procedure, Academic Integrity Policy, University Code of Conduct and Professional Staff Misconduct Guidelines. (36) Staff have a responsibility to: (37) Students have a responsibility to: (38) Deputy Vice-Chancellor and Vice-President (Academic and Student Life) staff have a responsibility to: (39) LTC staff have a responsibility to: (40) Data and Analytics Division staff have a responsibility to coordinate and maintain UOW’s Enterprise Data Warehouse, including: (41) The Learning Analytics Advisory Group has a responsibility to: (42) The Ethical Use of Data Advisory Group is considered the main forum for consultation with staff and students on this policy. (43) Refer to ‘Code of Practice for Learning Analytics’.Learning Analytics Data Use Policy
Section 1 - Purpose of Policy
Top of PageSection 2 - Application and Scope
Section 3 - Policy Principles
Top of PageSection 4 - Transparency in Learning Analytics Activities
Section 5 - Student Access to Learning Analytics
Section 6 - Student Privacy
Section 7 - Validity of Data and Analytics Processes
Section 8 - Enabling Positive Student Interventions
Section 9 - Minimising Adverse Impacts
Section 10 - Continuous Improvement of Teaching and Learning Activities
Section 11 - University Research
Top of PageSection 12 - Consequences of Breaching this Policy
Section 13 - Roles and Responsibilities
Staff
Students
Pro Vice-Chancellor (Students) Staff
Learning, Teaching and Curriculum (LTC) Staff
Data and Analytics Division (DnA) Staff
Learning Analytics Advisory Group
Ethical Use of Data Advisory Group
Section 14 - Appendix A: Approval Process – University Research Using Learning Analytics Data
Section 15 - Definitions
Word/Term
Definition (with examples if required)
Academic staff
Staff employed under the Academic Staff Enterprise Agreement.
At-risk student
A student with a personalised data-profile which includes evidence informed risk factors that can inhibit successful completion of studies.
DASH
Data and Analytics Self Service Hub. The UOW enterprise business intelligence platform.
Data mining
Extracting or mining knowledge from large amounts of data.
Data warehouse
A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process.
DVCA
Deputy Vice-Chancellor and Vice-President (Academic and Student Life)
HREC
Human Research Ethics Committee
Data and Analytics Division
Data and Analytics Division. A single unit within Information Management and Technology Services (IMTS).
Learning analytics
The measurement, collection, analysis and reporting of data about students and their learning contexts.
Learning analytics data
The aggregated dataset sourced from smaller datasets many of which originate in the numerous transaction processing systems in use at UOW.
Learning Analytics Advisory Group
A group established by the Deputy Vice-Chancellor and Vice-President (Academic and Student Life) with responsibility for reviewing and advising on the strategic direction and on operational matters at UOW regarding the deployment of learning analytics to support student learning.
Professional Services staff
Staff employed under the General Staff Enterprise Agreement.
Staff
All persons appointed by the University as academic or professional services staff .
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