UnitLevel 5Postgraduate

ITO5007 Introduction to data science for learning analytics

Faculty of Information Technology

ITO5007 Introduction to data science for learning analytics is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology. It isn't offered in 2022. It has no prerequisites and unlocks 1 unit.

Credit points
6
Offered in 2022
Other periods
Monash Online
Workload
12 hours
per semester

This is the 2022 handbook entry. See the 2027 entry.

Reviews

No reviews yet

No reviews yet. Be the first to review ITO5007.

Requisites

Before ITO5007

No prerequisites or corequisites.

After ITO5007

1 unit list ITO5007 as a prerequisite or corequisite.

Overview

This unit will focus on the key data science approaches as commonly used in learning analytics. Students will work on relevant datasets and develop skills in identifying suitable data indicators for specific contexts. This unit provides foundations for feature engineering to extract relevant indicators from raw data about learning. Relevant data analytics tools and techniques will also be introduced. This will provide students with experience in working on common tasks in learning analytics using data science approaches that are situated in established frameworks used for designing and evaluating learning environments.

Offerings in 2022

Teaching periodCampusMode
Teaching period 5Monash OnlineOnline

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Analyse the role of data in learning analytics;

  2. 2

    Identify and apply basic tools for performing exploratory data analysis, visualisation, and predictive modelling in learning analytics;

  3. 3

    Discuss and evaluate the legal and ethical issues due to the use of data science in learning analytics;

  4. 4

    Develop and critically assess a detailed plan for data science implementation in learning analytics.

Workload and teaching

  • Tutorials24 hours
  • Teaching approachActive learning
  • Teaching approachOnline learning

Minimum total expected workload equals 12 hours per week

independent learning, discussions, collaborative learning, and feedback & reflections.

Contacts

Chief Examiners
Dr Namrata Srivastava

Common questions

What are the prerequisites for ITO5007?

ITO5007 has no prerequisites.

What can I take after ITO5007?

ITO5007 is a prerequisite or corequisite for 1 unit, including ITO5010.

When is ITO5007 offered?

ITO5007 has no offerings listed in the 2022 handbook.

How much work is ITO5007?

The handbook expects about 12 hours of study across the semester. No students have rated its difficulty yet.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Information Technology
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Not available
Handbook years
202220232024202520262027