Learning Design and Research Methods/Statistics

James DalzielProfessor of Learning Technology &

Director, Macquarie E-Learning Centre Of Excellence (MELCOE)

Macquarie University, Sydney, Australia

james@melcoe.mq.edu.au

www.melcoe.mq.edu.au

Recorded presentation for ALTC National Teaching Fellowship

Background

• Recorded presentation to accompany main Learning Design workshop recordings for ALTC National Teaching Fellowship– See 3 Workshop recordings, and 2 Larnaca Declaration

recordings at http://www.slideshare.net/jdalziel71

– Learning Design context and Larnaca Declaration

• Reflections on Learning Design for Research Methods– Existing work on statistics and Learning Design

– Potential for sharing/adapting research methods templates

– Using data from students for teaching research methods

Learning DesignLearning Design

Learning Design Practice(LD-P)

Learning Design

Conceptual Map

(LD-CM)

Learning Design

Framework(LD-F)

The Larnaca Declaration on Learning Design:New Definitions for the future of the fieldSee www.larnacadeclaration.org for document

Learning Environment: Characteristics & Values

External Agencies InstitutionEducator Learner

All pedagogical approachesAll disciplines

Educational Philosophy

A range based on assumptions about the Learning Environment

Theories & Methodologies

Guidance Representation Sharing

Core Concepts of Learning Design

Tools Resources

Implementation

Program

Module

Session

Learning Activities

Level of Granularity

Teaching Cycle

Feedback Assessment Learner Analytics Evaluation

Learner Responses

Creating learning experiences aligned to particular pedagogical approaches and learning objectives

Challenge

Learning Design and Statistics

• While Research Methods is a broad area, the particular focus of this part of the Fellowship was teaching statistics and related research methods– Many students often find this a very challenging area,

especially those with less mathematical background, eg, many in psychology, and other social sciences

• Often statistics is assumed to be a “single learner” topic, so self-paced courseware is used, but Learning Design can bring collaborative learning to statistics

Learning Design and Statistics

• Bilgin & Petocz (2006). LAMS and Statistics Pedagogy– http://lams2006.lamsfoundation.org/pdfs/Bilgin_and_Petocz_LAMS06.pdf

• Examines 3 different sequences in 2 teaching contexts

“the LAMS sequences illustrated in this paper each contain several aspects of the range of media forms and corresponding learning experiences identified by Laurillard (2002, p90). For instance, the ‘placebo’ sequence (Figure 3) is narrative (reading the article on the web site), interactive (exploring the definitions of the words in the online dictionary), communicative (the group discussion of answers and identification of the ‘best’ one), adaptive (changing participants’ views in response to seeing the range of views from their group) and productive (the writing of the individual answers to the second and third questions).”

Learning Design and Statistics

• Bilgin & Petocz Identify the benefits of re-use and adaptation, and locate these in the wider scholarly research and teaching context

“Finally, we note that each sequence can be re-used either in exactly the same form (in later offerings of the same unit in following semesters – this has already been done with the ‘coin tossing’ sequence) or as a template in the same unit (for example, the ‘placebo’ sequence was based on an earlier sequence with the same structure investigating the notion of ‘median’) or by other lecturers in other units. In this way, the potential for the academic community to support teachers with new pedagogic ideas and approaches encapsulated in LAMS sequences or learning designs, is realised. In this way, the scholarly approach that we characteristically apply to academic research is also brought to bear on academic teaching and student learning”

Learning Design and Statistics

• So even though Learning Design is sometimes considered to be more relevant to social sciences/humanities, and less so for maths, this example illustrates all the same hope and ideals for Learning Design applied to statistics

• Benefits of collaborative learning in statistics

Learning Design and Statistics

• The second area of use, following on from collaborative learning, is the potential to use students’ own data as a basis for teaching statistics

• Foster greater engagement with difficult concepts by using data collected by students themselves (could be via survey, or laboratory data)

• Allow students to see how statistical analysis derives from the bedrock of their own individual data points

• Example from marketing statistics

Example of marketing statistics Learning Design – Using students’ own data for analysis task

Alternative example for laboratory statisticsStudents upload lab data via Task List tool

Future Learning Design system goal:Allow for automated data presentation after collection

Conclusion

• The potential of Learning Design for teaching statistics has already been recognised and implementat

• Use of students’ own data could increase engagement and understanding of how analysis related to individual data points

• Future system development could help automated data collection and re-presentation to students