Download and Installation 

Before you download the most recent prototype, please note that:

• This version is made available for prototyping purposes;
• The prototype is rapidly changing and there is no support for data loss at this point of the development, thus the use of this version is entirely at your own risk;
• Use of this prototype constitute agreement to the licence release

• Download the Zip file
• Extract the zip file to a desired folder
• Run the application by double-clicking Run.bat (on a PC) or LPP.jar (on OS X and Unix).
  Please note that it may take a few seconds to launch the application.

Download the LPP prototypes from our Google Code Repository.

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How to use LPP

(under construction)

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Feedback

Your questions, comments and suggestions are welcome. You can use our web submit form at www.c

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Key Features

• Flexibility to adapt to the needs of educational practitioners in different institutional contexts, while enabling the sharing of expertise across contexts;
• Experiment, share and analyse learning design;
• Link to online resources (e.g. Phoebe project, LO repositories, case studies, research findings, local information about learner needs);
• Use with learning design systems (e.g. LAMS, GLO).

Fig. 1 Mapping between components, e.g. to ensure appropriate linking between topics and outcomes. By ‘drawing' a line using the mouse, users can link topics (listed on the left-side of Fig 1) to selected outcomes (right-side). The visual layout clarifies the extent to which there is a mismatch between them. It becomes very obvious if there is a learning outcome that is not covered, and this forces consideration of whether it should be, and if so, how.

"The mapping principle is sound, and multiple mappings are important - really nice and visual"

Fig. 2 The schedule interface shows topics automatically inherited from users' previous input. Beside the list of topics is a ‘calendar-like' visualization, and below this are the outcomes previously linked to those topics for each week. The tool offers the functionality to schedule which topics are to be covered in which weeks: clicking on a ‘cell' for a topic, also highlights the corresponding ‘cells' for the linked outcomes for each week. With this visualization, users may reflect on the pattern of learning outcomes they are asking learners to tackle within a week. If they seem unbalanced, they can easily edit the schedule by clicking and dragging boxes representing topics. "I like this very much, because it's mapped in my topics for me and it's showing me them in weeks and it's showing where they can overlap." Fig. 3 Users select the teaching methods they   wish to use. They allocate the credit hours already input for   the Module across the selected methods (under 'Hours'). These are automatically distributed across the cognitive activities that each method elicits. For example, in this Fig, 20 hours of lectures have been allocated, and the Planner interprets this as 20 hours of attention, as the learning activity elicited. By contrast, the 19 hours for online asynchronous conferencing have been distributed as 5.7 hours of attention and 13.3 hours of discussion, meaning that for this teaching method learners spend some time reading, but a much greater proportion in active preparation for, participation in, or reflection on, discussion. Users may decide that this representation mis-describes, e.g. their lectures, and will edit the distribution of lecture hours to make it 15 attention and 5 discussion, if they organise their lectures in this way. The Planner records this as the interpretation of the meaning of lecture for this learning design.                     

"Would also think about it as a hand-over tool from one module convenor to another."

Fig. 4 At the session level, users are given  the  option  to  define  their learners'  needs,  and either  way, are asked to select from  a given list  of  needs  linked  to  existing learning designs that are relevant to their selected needs.

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Preliminary findings

Based on workshops conducted, lecturers' data include the following preliminary findings:

• The visual representations of learning design decisions and their consequences are welcomed, and workable
• The approach of offering default input for design decisions that users can edit or accept is an efficient way of enabling lecturers to work quickly to understand how to use the tool 
• Practitioners want integration with VLEs, and the means to manage the development and sharing of a large number of learning designs