Office for Digital Learning

Policy

learning analytics policy

Posted on: 25 Jul 2017

Introduction

  1. The collection and use of data about students and their learning is providing new opportunities for institutions to support learners and to enhance educational processes. Learning analytics systems present visualisations of student learning activity and provide predictions of attainment. These will be used at Ulster to assist current students in achieving their study goals, and to help us improve our overall provision of education.
  2. Ulster will use learning analytics to help meet the following strategic objectives aligned to the Academic Excellence priority of Ulster’s Five and Fifty Strategy.
    1. increasing numbers of students completing a programme of study within a specific time frame (retention) and increasing numbers of students who progress in and beyond education (progression).
    2. improving attainment (cumulative achievements and level of degree-class award).
  3. Ulster University will ensure that learning analytics is deployed for the benefit of students, with complete transparency about the data that is being captured, processed and used. All activities in this area will comply with Ulster’s Data Protection Policy ensuring compliance with the Data Protection Act 1998.

Responsibility

  1. Overall responsibility for learning analytics at Ulster is held by the PVC Education. Responsibility for relevant areas of activity is allocated as follows:
    1. The anonymisation or de-identification of data where appropriate - Director of Access, Digital and Distributed Learning.
    2. The collection of data to be used for learning analytics Director of Access, Digital and Distributed Learning.
    3. The analytics processes to be performed on the data, and their purposes - PVC Education.
    4. The interventions to be carried out on the basis of the analytics - PVC Education.
    5. The retention and stewardship of data used for and generated by learning analytics - Head of the Office for Digital Learning.
  2. Any analytics presented to students are intended to help them understand how their learning is progressing, and suggestions may be made as to how they can improve their practices. Students are responsible for assessing how they can best apply any such suggestions to their learning.

Transparency and consent

  1. Students are informed about how their data will be processed when they agree to the data protection consent notice upon registration. Data will be collected for learning analytics in compliance with Ulster’s Data Protection Policy. The statement reads:
    “the University will use the information which it holds about you to deliver your programme, to provide educational and support services to you, to monitor your performance and attendance and to collect feedback; and for management activities such as strategic planning, statistical analysis, equal opportunities monitoring and maintaining IT systems.”
  2. The data for learning analytics comes from two sources, the student record system and the virtual learning environment, Blackboard. The Student Guide to Learning Analytics will clearly specify:
    1. The data sources being used for learning analytics.
    2. The specific purposes for which learning analytics is being used.
    3. The metrics used, and how the analytics are produced.
    4. Who has access to the analytics, and why.
    5. Guidance on how students can interpret any analytics provided to them.
    6. The interventions that may be taken on the basis of the analytics.
  3. Students will be asked for their consent for any automated prompts or suggestions to be sent to them, based on the analytics. These may include emails, SMS messages or app notifications. Learning analytics is separate from assessment. Metrics derived from data sources used for learning analytics will not be used for the purposes of assessment.
  4. Learning analytics is separate from assessment. Metrics derived from data sources used for learning analytics will not be used for the purposes of assessment.

Confidentiality

  1. Personally identifiable data and analytics on an individual student will be provided only to:
    1. The student
    2. Ulster staff members who require the data to support students in their professional capacity.
    3. Blackboard who are processing learning analytics data on behalf of the institution. Ulster has put in place contractual arrangements to ensure that the data is held securely and in compliance with the Data Protection Act.
    4. Other individuals or organisations to whom the student gives specific consent.
  2. Ulster IT staff will have access to systems and data in order to maintain proper functioning of learning analytics systems rather than to access any individual’s data.

Sensitive Data

  1. The Data Protection Act 1998 defines categories of “sensitive data” such as ethnicity or disability. Any use of such data for learning analytics will be fully justified, and documented in the Student Guide to Learning Analytics.

Validity

  1. The quality, robustness and validity of the data and analytics processes will be monitored by the University, which will use its best endeavours to ensure that:
    1. Inaccuracies and gaps in the data are understood and minimised.
    2. The optimum range of data sources to achieve accurate predictions is selected.
    3. Spurious correlations and conclusions are avoided.
    4. The algorithms and metrics used for predictive analytics and interventions are valid.
    5. Learning analytics is seen is its wider context, and is combined with other data and approaches as appropriate.

Student Access to personal data

  1. Mechanisms will be developed to enable students to access their personal data, and the learning analytics performed on it, at any time in a meaningful, accessible format. Students have the right to correct any inaccurate personal data held about themselves.
  2. Students will also be able to view any metrics derived from their data, and any labels attached to them.
  3. On occasion it may be considered that access to the analytics may have a negative impact on the student’s academic progress or wellbeing. In these cases they may be withheld from the student. However, if the student requests it, all their personal data and analytics will be made available to them.

Interventions

  1. A range of interventions may take place with students. The types of intervention and what they are intended to achieve are documented in the Student Guide to Learning Analytics. These may include:
    1. Prompts or suggestions sent automatically to the student via email, SMS message or mobile app notification (subject to the student’s consent).
    2. Staff contacting an individual on the basis of the analytics if it is considered that the student may benefit from additional support.
  2. Interventions, whether automated or human-mediated, will normally be recorded. The records will be subject to periodic reviews as to their appropriateness and effectiveness.

Minimising adverse impacts

  1. The University recognises that learning analytics cannot present a complete picture of a student’s learning, and that predictions may not always be accurate.
  2. Students will retain autonomy in decision making relating to their learning; the analytics are provided to help inform their own decisions about how and what to learn.