Master thesis spring 2010 - Anders Gimmestad Gule

Calendars as User Context Providers in an E-learning

Environment

Supervisor: Rune HjelsvoldApropos-Internett: Dag Olaf Berg

outlineintroductionproblemmethodologypart onepart twoconclusionfuture work

Web courses are often neglected by the students/participants, other tasks are prioritized.

Context-aware systems tries to read a context (situation), and act accordingly.

With a known context (past, present or future) a context-aware LMS could assist the student in the process of planning/suggesting course modules.

Introduction - Problem - Methodology - Part one - Part two - Conclusion - Future

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Context in an E-learning environment

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«Context is any information that can be used to characterize the situation of an entity. An entity is a person, place or object that is considered relevant to the interaction between a user and a application, including the user and applications themselves.»Anind K. Dey, 2001 - «Understanding and using context»

Context

Potentially, a calendar can describe an entity’s (who) location (where) and it’s resources (what) in a time set (when).A calendar potentially form a reliable and stable source for context data.

Calendar as a sensor

Related work- centered around the algorithms.- little or no literature on the reliability of calendars.Context is inconstant - it always changes.- hard to capture correctly.Calendars are made by people - people are lazy.- content and details are user dependent.- can calendars be considered reliable?Adapting to user context- context features are not determined or not assessed.- how do the features affect the results when utilized?

What is the problem?

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Q1 How do the correlation between different user types and users’ motivation affect the contents in their calendars?

Q2 How suited are real-world calendars as candidates for user context extraction?

Q3 What user context features should be considered in a context-aware planning algorithm, and how do they affect the result?

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What are the unknowns?

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Calendar analysis- gather calendars- compare- analyze

Feature identification- interviews- analysisPrototype testing/analysis- use cases- scenarios

Literature research

Study of users- interviews- internet-survey

Part one Part two

Methodology

Study of calendar users

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StudentsMotivated by:- personal gains- organizing, rememberProfessionalsMotivated by:- job environment- organizing and managing

Survey33 participants, 10 students - 23 professionals

Study of calendar users (cont.)

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Motivation and contentShared calendars

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Professionals have strong reasons for motivation (, and a shared calendar strengthens this motivation further).- consequence; a professional’s calendar is a «better» than a student’s- we need to separate students and professionals in further analysis.

Significant correlation between motivation and calendar details/accuracy.- a motivated user generates a «good» calendar.- users who understand the benefits tend to provide a more detailed calendar

What do we do now?

Study of calendar users (cont.)

Points of interest- categorization of entries- entry content- entry clusters- users

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Study of calendars

Analysis13 people x 2 weeks of calendar data- 8 professionals, 5 students- 26 weeks, 442 entries

how much information can be extracted about the user?

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Study of calendars (cont.)Entry categorization 38.9 % (172 of 442) unidentifiable entries- 68.6 % (83 of 121) unidentifiable student entries- 27.7 % (89 of 321) unidentifiable prof. entries

Entry content Location - 41 % (172 of 442) with location attribute- place names and room number most commonly used as descriptor. - not enough Descriptor - «meeting with John»- high quantity, but low quality

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Study of calendars (cont.)

ContentProblem: low quality of entry descriptors.Suggested remedy: User ModelUsersUsers who:

... produce small amount of entries and minimal level of detailed content. (50 %, mostly students).... only include the most important details (35 %).... act highly organized and produce a high amount of detailed content (15 %).

Confirms our initial results form the survey.What do we do now?

Conclusion of part one:Calendars have a potential

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context features- day- time of day- ideal/bad times- reserved times- time between entries- observations

Analysis10 volunteers, interviewed about their planning preferences.- 5 students and 5 professionals.- questions/conversation- practical task

User planning behavior

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User planning behavior (cont.)

Context features- all features are significant to the participants.- students and professionals again have different results.Planning approaches- professionals prioritize the planning according to importance, students according to personal preferences (sleep, food etc.).- professionals reorganize and tweak their calendar, students do not.- plans according to the situation (before/after lunch etc.)

Utilizing context features

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proof of concept - planning assistant prototype«Plan a course module according to the identified context features.»Prototype- categorization procedure - assess the open slots in the calendar- which day- time at day- time before and after the proposed slot- entries (context) before and after the proposed slot- suggests alternatives to the user

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Preliminary conclusionsPart one- calendars from motivated users with the presence of a user model, can be considered as reliable sources for user context extraction (a professional’s calendar is best suited for this purpose).Part two- day, time at day, time between entries, personal and other users’ activities are significant context features for the interviewees when planning.- professionals and students differ, other user groups may also.- Uncategorized entries have a large influence to the accuracy of the prototype’s accuracy.

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Future work

- A categorization/classification algorithm, that can obtain user input and feedback.

- Further analysis on the context features’ importance. Which is more important than the other?

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