Supporting learning during an MDSI internship

Internship subjects provide an important opportunity for students to prepare for the workforce by developing their professional skills through work-based learning. During their internships, MDSI students engage in a professional workplace context and undertake experiential work-based learning to develop their professional identities, together with an understanding of the professional practice of data science.

Alongside the tasks and duties undertaken for their internships, students also complete academic assessments for their internship subjects. During the internship, students will observe and learn about the application of data science, participate in workplace tasks, and should receive ongoing feedback from their workplace supervisors. Students will also critically reflect on their participation, project progress and their responses to feedback and business requirements in a reflection report. This allows them to engage in a unique learning journey in a workplace-based learning environment.

How to support students with their assessments

For their Data Science Internship subjects MDSI students submit three assessments, here is how you can support your intern with these academic requirements:

• Internship Plan: Within the first 4 weeks of the placement, the student will need to create an Internship Plan that outlines their learning objectives for the internship. As part of this plan, interns need to agree a timeline for their internship activities, the deliverables, and criteria for its completion with their internship supervisor (you). You will be asked to sign off on this plan before it is submitted to TD School (by the student) as an assessment task.
• Placement Report: At the end of the internship, the student will submit a report for assessment to TD School, this will outline the work they have undertaken (deidentified, no sensitive information or data to be shared), reporting on outcomes and outputs. You can help the student with this by reviewing this report, if asked, and offering feedback to help them distil their work and accurately measure success.
• Reflection Report: Submitted at the end of the internship, this report is an opportunity for students to map their data science capabilities, identify their professional learning from the placement and consider career pathways options. See suggested activities below for how to support students to validate their learning across the internship.

How to support students with their professional development

Here are two keys ways that supervisors can look to support students’ professional learning throughout an internship:

1. Discuss student's individual learning goals at the start of the placement and identify how and where they can help facilitate this learning.
2. During the internship offering regular times for feedback, both casual and more formal.

How to support interns and their professional learning outcomes

1. Start with a conversation

On the first day of the internship, create time and space for a one-on-one conversation.

• Discuss the student’s learning goals and reasons for undertaking this internship. Consider or plan how and where you can support or facilitate this development.
• Ask the student to talk about their skills, knowledge, and experience in relation to what they think you and the broader sector are looking for as employee attributes.
• Help the student identify any gaps and offer advice about how their skills and goals match the needs of your organisation and where should they focus some energy for development.
• Talk to the student about professionalism in your industry; how do your employees communicate and interact? What should they do if they need help or advice? What should they do if they are running late or fall behind on a project/deadline?

2. Help the student seek regular feedback

• Introduce the student to members of staff who can provide them with feedback on their work.
• Help the student to create time and space for feedback regularly throughout the internship.

3. Be curious about the student’s skills, methods and approaches

• Provide opportunities for the student to be challenged in their work tasks.
• Be open to mutual learning opportunities, you could ask the student to share some of their learnings from their degree with you and your team; for instance how they might approach ethical data considerations or human-centred design approaches to data.

4. Reflect on the experience together

• Discuss the internship and the student’s performance: what did they do well, where could they improve and why this is important. You can use the professional indicators from the MDSI UTS Student Evaluation form to support this conversation.
• At the end of the placement please complete the evaluation form to provide feedback to both the student and TD School on the student’s professionalism, and the overall internship experience. To note your responses in the evaluation contribute to the student’s grade for their Data Science Internship subject, so the Subject Coordinator may reach out after the evaluation has been submitted to discuss your feedback.
• Ask the student what they enjoyed about the placement and whether it aligned with their expectations.
• Discuss options for how the student can artefact the internship and their learning. This might include adding to their LinkedIn profile, including an example of their work from the internship into their portfolio (depending on confidentiality/IP restrictions).