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Student Academic Performance Evaluation Procedure

Section 1 - Introduction

(1) The University of Newcastle (University) acknowledges the need to support students throughout the duration of their studies. The University uses learning analytics for monitoring students academic performance to facilitate adaptive and responsive educational design and learning environments, incorporating information from students academic progress, engagement, results, and enrolment trends.

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Section 2 - Purpose

(2) This Procedure establishes how the University will use learning analytics to evaluate students academic performance determine appropriate outreach activities to support students in their studies.

(3) This Procedure supports the Student Academic Performance Evaluation Policy and should be read in conjunction with the Policy.

(4) In the event of an inconsistency between the Student Academic Performance Evaluation Procedure and a Rule or a Schedule to a Rule, the Rule or Schedule made by the Council will prevail to the extent of the inconsistency.

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Section 3 - Scope

(5) This Procedure applies to students enrolled in an enabling or coursework program at the University, and should be read and understood by the academic, professional, and executive staff who oversee and support student learning.

(6) This Procedure applies to the Joint Medical Program (JMP). In the event of an inconsistency between this Policy and the policies and procedures specific to the JMP, the policies and procedures of the JMP will prevail to the extent of the inconsistency, unless the matter relates to a delegation of authority.

(7) This Procedure does not apply to Higher Degrees by Research (please see Higher Degree by Research Policy).

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Section 4 - Use of Learning Analytics

(8) Learning analytics supports the analysis of existing data from the University systems, including but not limited to student information systems, student feedback systems, and the learning management system.

(9) Data related to student engagement with counselling services or other confidential student support services will be governed by professional confidentiality norms and not be made visible to end users. 

(10) Using learning analytics, the University will identify students who are at-risk of not successfully completing a course or program. The risk factors used in learning analytics could include, but are not limited to:

  1. Academic – repeated attempts; not having completed courses listed as assumed knowledge; and/or a high number of previous fails (FF) and withdrawals (W).
  2. Engagement – late enrolment; infrequent or no engagement with the learning management system; failure to submit assessments; late submission of assessments; and/or failure to meet attendance requirements. 
  3. Progress – course enrolment resulting in a fail (FF) or withdraw (W) grade. 

(11) Students who fail or withdraw from the same course for a second or subsequent time will receive communications, and may be referred to the College Progress and Appeals Committee under the provisions outlined in the Student Academic Progress Procedure. 

(12) Learning analytics will be used to enable delivery of targeted outreach activities, including but not limited to:

  1. outreach activities administered by the Course Co-ordinator, or their nominee; and
  2. outreach activities administered centrally. 
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Section 5 - Implementation

(13) Outreach activities will occur at defined points within the term, with reference to commencement, census date, examination period, and fully graded date, or at other times throughout the term as relevant to the course or program. 

(14) Learning analytics will enable management of course risk factors and individual student performance.

(15) The Course Co-ordinator, or appropriate staff member, will contact students flagged with risk factors.

(16) Outreach activities may include but is not limited to referral to resources and support outlined in the Support for Students Policy.

(17) Resources to support Course Co-ordinators and appropriate staff will be made available internally via SharePoint.

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Section 6 - Oversight and Quality Assurance

(18) An annual report will be submitted to the Teaching and Learning Committee and Academic Senate by the Pro Vice-Chancellor Education Innovation during Semester 1 which will provide aggregated data on the previous year’s trends, measures, demographic, and associated retention/attrition rates, as well as related data derived the learning analytics dashboards.

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Section 7 - Roles and Responsibilities

Who Responsibility
Students
  1. Provide relevant information to the University when requested.
  2. Engage with support services and the learning management system.
  3. Read University correspondence.
  4. Be aware of responsibilities as detailed in course outlines and course materials.
Course Co-ordinators
  1. Engage with training and professional development on the interpretation and ethical use of learning analytics data.
  2. Use an evidence-based approach to monitor learning analytics dashboards for issues or trends that arise.
  3. Direct students with course risk factors to relevant support services in a timely manner.
  4. Use learning analytics data to stimulate continuous improvement in course delivery, student engagement, and the student experience.
Program Convenors
  1. Use course-based learning analytics to inform program design and coherence.
Learning Design and Teaching Innovation
  1. Provide ongoing training and development for academic staff to:
     - monitor and respond to learning analytics;
     - improve course design and delivery.
Student Central
  1. Coordinate communications to connect students with support services.
  2. Identify and assist students at-risk of not making satisfactory progress as defined in the Student Academic Performance Evaluation Policy and the Student Academic Progress Procedure.
Associate Dean (Education) Monitor College-level aggregated learning analytics including summary data of student risk profiles and support Course Co-ordinators and Program Convenors.
Heads of School Ensure that Course Co-ordinators use an evidence-based approach to monitor learning analytics dashboards for issues or trends that arise, and to direct students with course risk factors to relevant support services in a timely manner.
Pro Vice-Chancellor Education Innovation
  1. Promote learning analytics dashboards and staff roles and responsibilities.
  2. Monitor and report on learning analytics to encourage continuous improvement and address key performance indicators relating to engagement (risk) and retention (success). 
  3. Coordinate reporting and compliance with the Support for Students amendments to the Higher Education Support Act (2003).
  4. Identify and refer potential areas of concern as appropriate.
Strategy, Planning and Performance
  1. Oversee the development, administration, and ongoing improvement of learning analytics dashboards.
  2. Respond to stakeholder requests for system access, repairs, or enhancements.
Academic Division General Manager and Academic Registrar
  1. Ensure that University systems accurately capture data to inform learning analytics activities.