Ako Aotearoa NPF15-008: 
Building an evidence-base for teaching and learning design using learning analytics data




PROJECT TEAM MEETING:

The project team for NPF15-008 will be meeting face-to-face in Wellington, NZ on the 18th June, 2015. We timed our meeting to co-incide with LASI meetups around the world during the week of 15th June.
http://solaresearch.org/events/lasi/lasi2015/
We invite our LASI2015 colleagues  to reflect on what data and in particular learning analytics data, means for teachers and learning designers. Go to the Taxonomy Sketch to join us online and share your perceptions and experiences in your own time.

Colleagues from NZ tertiary institutions are also welcome to contribute case-studies to the project. Please contact A/Prof Cathy Gunn, University of Auckland or Dr Jenny McDonald, University of Otago if you would like to contribute a case study to this National Project.

About the project:

Learning analytics research uses large, anonymous sets of passively collected system data as an objective source of feedback on student interactions with online learning activities. Access to this kind of hard evidence allows teachers to understand the influence of different activities and therefore to design more effective and timely learning tasks. The data is collected by elearning systems as a matter of routine. However, extracting useful information from it requires a level of data literacy that many teachers do not have. Our project will use participatory action research case studies to develop ways to translate learning analytics data into useful information for tertiary teachers and learning designers.  This will enhance outcomes for learners through better design, and contribute to the knowledge base for effective tertiary teaching and learning in Aotearoa. 

Aims

The aim of the research is to identify teaching and learning design questions that can be answered by the learning analytics data available through common elearning systems. Case studies will allow us to explore how the raw data required to answer these questions can be presented as accessible information for teachers.

The two-phase research project will:

  • Identify the learning analytics data currently available through common learning management systems such as Moodle or BlackBoard, and elearning tools such as peer and online assessment and tutorial dialogue systems.
  • Generate and disseminate a taxonomy of analytics data to guide educators towards selection of data appropriate to the questions they want to answer or explore.
  • Distinguish which analytics data can illuminate the relationship between learning design, i.e. a teaching plan with intentions and assumptions about what students will learn; intermediate learning outcomes, i.e. learning strategies, engagement in activities and construction of new knowledge; and final learning outcomes, i.e. what students can demonstrate they have learned.
  • Initiate sustainable changes in practice within the academic institutions represented by our research team and promote similar changes in others.

Design / Methodology

In the scoping phase of the study, we will identify and categorize the learning analytics data collected by each type of system and use this as the basis to develop a taxonomy representing the range of data types collected, ways to extract meaning, and the permissions or restrictions that may apply to their use. The project team will liaise with senior institutional staff to negotiate access to data that is centrally hosted or managed. This initial contact will also be designed to encourage institutional buy-in to new practices involving the use of analytics data when later stages of the project produce evidence of benefits for learners and teachers.

In phase 2, we will use case studies to explore how teachers interpret learning analytics data as feedback, and use the insights provided to develop or modify learning designs. Up to eight participatory action research case studies will be selected from the participating institutions. Teaching staff who use the elearning tools identified in Phase 1 will become co-investigators in Phase 2. This collaborative research approach will support the aim to drive sustainable change in teaching practice within participating institutions.

Intended outcomes

We will produce:

  • A taxonomy of learning analytics data collected by common elearning systems with guidelines for use of this information in teaching and learning design.
  • Design frameworks, reusable digital resources including online tutorials and templates, and case study examples for the use of learning analytics data as an input to learning design.
  • A series of interactive workshops on the extraction and use of learning analytics data for tertiary teachers and learning designers.
  • Journal articles and conference papers describing the contribution of learning analytics data to teaching and course design, and to the field of learning technology research.
  • Communication and dissemination strategies designed to encourage extensive use of the taxonomy and design information provided by learning analytics data.
  • Policy recommendations to promote the use of learning analytics data in teaching and learning design.