Presentation of the Defence of the PhD Dissertation "Towards a personalised virtual library: indications from navigational and personal information behaviour of e-learning students".

1. Towards a personalised virtual library:
indications from navigational
and personal information behaviour
of e-learning students
Defence of the Doctoral Dissertation
PhD student: Núria Ferran Ferrer
PhD Supervisors: Dr. Julià Minguillón and Dr. Mario Pérez-Montoro
Doctorat en Informació i documentació en l'era digital
Programa interuniversitari de doctorat 2006-2008 (UB-UAB)
Barcelona 9th of February, 2010

2. Overview
1. Introduction
2. Literature Review
3. Purpose and significance of the study
4. Hypothesis and research questions
5. Methodology
6. Hypothesis 1 (Papers I and II): research strategies and results
7. Hypothesis 2 (Papers III and IV): research strategies and results
8. Conclusions
2

3. 1. Introduction
• Study of information behaviour:
– Social and economic perspective:
• Informational society (Castells, 1999)
– Individual perspective:
• Personal Information Management (Jones, 2007)
Design of virtual environments
• Better understanding of the new user in the new digital
revolution (Rowland and Nicholas, 2009)
3

4. 2. Literature review
• Research on information behaviour:
– Human actions in relation to information souces and channels,
including both passive and active information seeking and the use of
it (Fisher and Julien, 2009) or its transfer (Wilson, 1999), as well as
the behaviour aimed at avoiding information (Case, 2002)
– Three consitutent elements: Need / Search process / Use
– Focused on searching in academic/research contexts
• Study of information literacy:
– Rare to find info behaviour and info literacy together
– Literates: acquired appropriate info. behaviour (Boon, 2007)
– The acquisition of this expertise may take place in a context and then
be transferred to the others (Lloyd, 2006). No studies about transfer
of competencies between contexts
4

5. 3. Purpose and significance of the study
• This research work is focused on:
– Information actions: search, but also manage and use
– Contexts: academic, but also workplace and daily life
– Information behaviour linked to information literacy
– Transfer of information-related competencies between contexts
5

6. 3. Purpose and significance of the study
• Life-wide learning in knowledge society:
– Students: personal/professional reasons, wide range situations,
through life
– Information literate individuals are ready for LLL, employment, active
citizens
• Overload of information:
– Personalised information delivery systems:
• Effectiveness and effiency
• User satisfaction, needs and requirements
• Power of user community
• Need for usable desings according to the context and behaviour
6

7. CONTEXTS
Basis Academic
Workplace
Daily life
USERS
Virtual Learning
Environment
Learning
process
INFO.
CONTENTS
SERVICES
(personalised)
7

8. 4. Work hypothesis and questions
Hypothesis 1: The navigation behaviour of the users of a
virtual library generates information for offering personalised
services.
a) How can the elements of a personalisation system of a virtual
library be semantically represented by the data coming from users'
navigational behaviour?
b) How can the information behaviour of e-learning students be
reused for rating learning objects?
c) What metadata fields can be automatically filled from analysing
user interactions with learning objects?
8

9. 4. Work hypothesis and questions
Hypothesis 2: E-learning students can adopt different personal
information behavioural patterns in their academic, workplace
and daily life contexts, while the information-related
competencies acquired in any of the contexts are transferred to
the other contexts.
d) What are the variables involved in the different patterns of
information behaviour of e-learning students?
e) What are the personal information behaviour patterns of e-learning
students in all their contexts of action?
f) Is it possible the transfer of information-related competencies
from/to academic, daily life and workplace contexts?
9

10. 5. Methodology
Multiple research strategies Publications
- Process of designing ontologies
Paper I
- Focus Group
Hypothesis 1
- Log analysis Paper II
- In-depth interviews Paper III
Hypothesis 2 - Incident cases
- Content analysis Paper IV
Multiple methodology approach:
• Quantitative: Way of doing. Real information behaviour
• Qualitative: Way of being. Reasons of the behaviour
10

11. 6. Hypothesis 1. Paper I
FERRAN, N.; MOR, E.; MINGUILLÓN, J. “Towards personalization in
digital libraries through ontologies”, Library Management Journal, 2005,
vol. 25, no. 4/5, p. 206-217.
ISSN 0143-5125
• Purpose
To describe those elements to buid a
personalised info. delivery system
integrated in VLE
• Approach
Use of ontologies to describe the
relationship between all those which
take part in a DL scenario of use
11

12. 6. Hypothesis 1. Research strategies
• Basic steps to design ontologies (Denny, 2002):
12

13. 6. Hypothesis 1. Results (User Model)
13

14. 6. Hypothesis 1. Results (Navigation Model)
14

15. 6. Hypothesis 1. Paper II
FERRAN, N.; CASADESÚS, J.; KRAKOWSKA, M.; MINGUILLÓN, J.
“Enriching e-learning metadata through digital library usage analysis”,
The Electronic Library, 2007, vol. 25, no. 2, p. 148-165. ISSN 0264-0473
• Purpose
To propose and evaluate an automated technique to obtain
non-authoritative metadata to rate LO
in order to improve their description and support
personalisation
• Approach
Tracking user navigation behaviour with LO
15

16. 6. Hypothesis 1. Research strategies
• Data gathered automatically:
– Non intrusive and without filters
– Raw data generated by Virtual Campus web server (Apache) by
default
• 2 million log lines per month (Feb-June 2006), 38,000 users
• Custom made application
• Focusing on the records of 2 virtual classrooms: 350
students
• Each session was analysed regarding access to the
classroom and what actions were performed in the DL
• Interactions with specific LOs were analysed in detail
• Real information behaviour: no partialities of laboratory, not asking
for active participation, natural environment
• Privacy assured by identifying only HTTP sessions, not users
16

17. 6. Hypothesis 1. Results
• Log file analysis of the navigational behaviour of LO:
– Some resources were never used:
• Poor description
• Not useful for the learning process
– Navigation followed time patterns
– Students followed the learning plan
17

18. 6. Hypothesis 1. Results (time pattern)
• Examples of Resource usage: Navigation differs over time
• Number of downloads per day of 2 LOs:
Drop/sustained
Weekends
Holidays
18

19. 6. Hypothesis 1. Results (Learning plan)
• Examples of learning process' monitoring
• Evolution of total number of downloads to 2 LOs:
4/5 days
between
LO accesses
19

20. 6. Hypothesis 1. Results
• Authoritative / non-authoritative metadata
• Selection of LOM non-authoritative fields that may be enriched
from user navigation data:
1.5. Keyword 5.8. Difficulty
1.7. Structure
5.9. Typical learning time
1.8. Aggregation level
3. Metadata 7. Relation
5. Educational 9. Classification
5.1. Interactivity type
5.3. Interactivity level
20

21. 6. Hypothesis 1. Results
• Example of metadata enrichment through LO usage:
LO described as independent chunks of information
Usage data: may reveal relationships with other LO's
LOM 1.7. Structure and 1.8. Aggregation level
21

22. 6. Hypothesis 1. Summary
Academic
Workplace
Daily life
actions
User preferences/features
Model profile
Virtual Learning USERS
Environment Navigational behaviour
Learning Qualitative: micro-scenarios
Interaction library uses
process
Quantitative: log analysis
INFO. CONTENTS
SERVICES
Repositories Metadata
22

23. 7. Hypothesis 2. Paper III
FERRAN, N.; GUERRERO-ROLDÁN, A.; MOR, E.; MINGUILLÓN, J.
“User Centered Design of a Learning Object Repository”. M. Kurosu
(ed.): Human Centered Design, HCII 2009, Lecture Notes in Computer
Science, no. 5619, p. 679–688.
ISBN 978-3-642-02805-2
• Purpose
To describe how to obtain information about user
information behaviour to improve the design of LOR
through UCD
• Approach
Qualitative approach (interviews and content analysis)
23

24. 7. Hypothesis 2. Paper IV
FERRAN, N.; PÉREZ-MONTORO, M. La Gestión de la Información
Personal en usuarios intensivos de las TIC, El Profesional de la
Información, 2009, vol. 18, no. 4, p. 365-373. ISSN 1386-6710
• Purpose
To offer an analytical model of information behaviour patterns of e-
learning students in their three contexts (AC, WP, DL)
• Approach:
Qualitative (interviews and content analysis)
24

25. 7. Hypothesis 2. Research strategies
• Random selection of the population under some criteria:
– gender, age, profession, disciplines, semesters, num. subjects,
family responsibilities and information literacy
– Short phone interview to generate sample. Email incident cases
(3 contexts)
• 24 in-depth semi-structured interviews on e-learning students UOC
(60-90 min each), Oct 07. 2 set trials (behaviour/context)
• Content analysis: 2 coders, NVIVO 7.0, reliability test (Krippendorff,
2004). Codebook with 10 categories
25

26. 7. Hypothesis 2. Research strategies
• Codebook
Categories involved in the Information
Contexts
different information patterns actions
Information-related competencies
Access Academic
(expert / non-expert)
Attitude
Management Workplace
(implicated / uninvolved)
Cognitive style
Use Daily life
(disciplined / chaotic)
ICT use perceptions
(enthusiastic / realistic / critical)
26

27. 7. Hypothesis 2. Research strategies
• Access to information:
– Gather and retrieve information. Needs
• Management:
– Treatment: applying existing organisation or classification systems
– Integration: interpreting and representing information
– Evaluation: quality, relevance, usefulness and efficiency of info
• Use:
– Creation: generate info, adapting, designing, inventing...
– Communication: effective transmission using appropriate media,
according to specific aims or recipients and to understand issues of
copyright and plagiarism
• Contexts: Academic, Workplace and Daily life
27

28. 7. Hypothesis 2. Research strategies
• Information-related competencies (expert / non-expert):
– knowledge, experience, skills, etc. to find, evaluate and use
information effectively
• Attitude:
– related with relational patterns (interpersonal / intergroup) and
personality traits (instinct, need, etc.):
• Implicated: essentially motivated to learn or seek
• Uninvolved: need a reward or punishment
• Cognitive style:
– personality aspect in relation with knowledge creation
• Disciplined: meticulous, focus on process
• Chaotic: follow their own rules, focus on results
• ICT perceptions (ICT as enabler, no priority or reservations)
• Enthusiastic, Realistic and Critical
28

29. 7. Hypothesis 2. Results
• Access to information vs context:
– Academic: “The university gives me everything so I do not need
to bother about searching for more”
– Workplace: The importance of the corridor
– Daily Life: “I control the Internet; it is not the Net which controls
me”
• Management of information vs context:
– Academic: Use of the tools in purposes unexpected when
designed
– Workplace: “We cannot take risks”
– Daily Life: “No need for managing it”
29

30. 7. Hypothesis 2. Results
• Use of information (communication) vs contexts:
– Academic: email
– Workplace: Everything is informal
– Daily life: Fridge-door as a communication platform
• Information-related competencies vs context:
– There is a strong relationship between the IL in Daily Life and
Workplace contexts
– There is no association between being expert or non-expert in the
academic context and the other two contexts
30

31. 7. Hypothesis 2. Results
• Attitude (Implicated / Uninvolved) vs context:
– Half of the participants had an implicated attitude in the three
contexts at the same time
– The other half were found to be implicated in the professional
and daily life contexts while uninvolved in the academic
• Cognitive style (Disciplined / Chaotic) vs context:
– Clearly different upon the context:
• Workplace: disciplined style prevails
• Daily life: the chaotic predominates
• Academic: both styles are equally abundant
• ICT Perceptions:
• Almost all cases coincident in being enthusiastic
31

32. 7. Hypothesis 2. Results
Behaviour patterns: 75% of participants were either disciplinated-implicated
or chaotic-uninvolved in the academic context.
Cognitive style ⋅ attitude = FOUR information behaviour patterns
Disciplined
EX
HA
E
U IV
CT
ST
EA
IV
E R
Attitude Implicated Uninvolved
E PA
T IV SS
AC IV
PRO E
Chaotic
Cognitive style
32

33. 7. Hypothesis 2. Results
• Information Behavioural Patterns (cognitive style / attitude)
EXHAUSTIVE: Disciplined / Implicated:
– Active when searching, managing and using information, finding
attractive these activities
– When they learn or improve some skill in one context they are
very talented for transferring them to the other contexts
– They use newish and innovatory tools
– But they need a roadmap, they appreciate guidelines and
knowing the process for getting the expected results
“...if I follow the marked steps, I am successful”
33

34. 7. Hypothesis 2. Results
Disciplined
EX
HA
E
IV
U
CT
ST
EA
IV
R
E
Attitude Implicated Uninvolved
E PA
T IV SS
AC IV
PRO E
Chaotic
Cognitive style
34

35. 7. Hypothesis 2. Results
• Information Behavioural Patterns (cognitive style / attitude)
PASSIVE: Chaotic / Uninvolved
– Users that are inconstant with procedures
– Need to adapt their internal rules to the regulations of the
contexts
– “I receive the didactical material at home but I do not need to open
the package”
– They need an environment that allows them to choose from a
wide range of processes to reach similar results
35

36. 7. Hypothesis 2. Results
Disciplined
EX
HA
E
IV
U
CT
ST
EA
IV
R
E
Attitude Implicated Uninvolved
E PA
T IV SS
AC IV
PRO E
Chaotic
Cognitive style
36

37. 7. Hypothesis 2. Results
• Information Behavioural Patterns (cognitive style / attitude)
REACTIVE: Disciplined / Uninvolved
– They need to feel secure with the tools, feel that they have the
knowledge and skills
– They act when “the teacher tells me which activities are useful for
evaluation”
– They transfer processes between contexts, but they use the
predetermined tools offered by each context
37

38. 7. Hypothesis 2. Results
Disciplined
EX
HA
E
IV
U
CT
ST
EA
IV
R
E
Attitude Implicated Uninvolved
E PA
T IV SS
AC IV
PRO E
Chaotic
Cognitive style
38

39. 7. Hypothesis 2. Results
• Information Behavioural Patterns (cognitive style / attitude)
PROACTIVE: Chaotic / Implicated
– They apply different processes and tools to different contexts,
not for standardizing their behaviour but as a personal feature
– They use the newish tools if they are more open, flexible and agile
– “I do not keep a directory, the Internet is already the directory”
39

40. Academic
Workplace
Daily life Hypothesis 2. Summary
Actions
User profile
Preferences/
USERS Model features
Virtual Learning Info. behaviour
Environment EXHAUSTIVE
Patterns PROACTIVE
REACTIVE
PASSIVE
Learning Qualitative: interviews and
process Interaction content analysis
INFO. CONTENTS
Quantitative: usage log
SERVICES mining
Repositories Metadata
UCD Competencies
40

41. 8. Conclusions
• Hypothesis 1: The navigation behaviour of the users of a
virtual library generates information for offering personalised
services.
Research question:
a) How can the elements of a personalisation system of a virtual
library be semantically represented by the data coming from users'
navigational behaviour? (Paper I)
41

42. 8. Conclusions
a) Using the information relevant to the process of searching and
browsing, the elements that determine the requisites of a
personalised virtual library embedded in an e-learning environment
are the following:
– User profile: including personal information, user preferences and
navigational history.
– Navigational profiles: data from the navigational behaviour of the
digital library users.
42

43. 8. Conclusions
• Hypothesis 1: The navigation behaviour of the users of a
virtual library generates information for offering personalised
services.
Research question:
b) How can the information behaviour of e-learning students be
reused for rating learning objects? (Paper II)
43

44. 8. Conclusions
b) Regarding the resources involved in the learning process, they can be
rated in an automated way based on registering navigational
actions of students.
In this way, their information behaviour within each session in the virtual
campus can be analysed and the access to each particular learning
object can be studied:
– Even without the special recording utilities in the virtual
campus, the interaction of students with learning objects
can be tracked by analysing server log files where all
HTTP requests are recorded by default.
44

45. 8. Conclusions
- More advanced potentialities are limited by the
anonymity of the students. In this sense, a more in depth
analysis would require recording an unambiguous
identification of the student in each session, not just his
or her IP address, while dealing with privacy concerns.
45

46. 8. Conclusions
• Hypothesis 1: The navigation behaviour of the users of a
virtual library generates information for offering personalised
services.
Research question:
c) What metadata fields can be automatically filled from analysing
user interactions with learning objects?(Paper II)
46

47. 8. Conclusions
c) From the evaluation of the interactions between users and contents, a
selection of Learning Object Metadata (LOM) fields can be
automatically generated and be further used as non-authoritative
metadata for rating those learning objects.
– These are the selected LOM fields:
1.5. Keyword 5.8. Difficulty
1.7. Structure
5.9. Typical learning time
1.8. Aggregation level
3. Metadata 7. Relation
5. Educational 9. Classification
5.1. Interactivity type
5.3. Interactivity level
47

48. 8. Conclusions
• Hypothesis 2: E-learning students can adopt different
personal information behaviour patterns in their academic,
workplace and daily life contexts, while the information-related
competencies acquired in any of the contexts are transferred to
the other contexts.
Research question:
d) What are the variables involved in the different patterns of
information behaviour of e-learning students? (Paper III)
48

49. 8. Conclusions
d) As the first step towards the design of a personalised information
delivery system, a User Centred Design (UCD) approach can be
applied for planning and developing a learning object repository:
• Interviews and log analyses are complementary methodologies for
gathering user requirements to obtain a service adapted to user
profile and context of use.
49

50. 8. Conclusions
• Hypothesis 2: E-learning students can adopt different
personal information behaviour patterns in their academic,
workplace and daily life contexts, while the information-related
competencies acquired in any of the contexts are transferred to
the other contexts.
Research question:
e) What are the personal information behaviour patterns of e-learning
students in all their contexts of action? (Paper IV)
50

51. 8. Conclusions
e) The personal information behaviour of e-learning students can be
classified into four patterns taking into account their attitudes and
cognitive approaches:
• This user categorisation can be stored in the user profile to feed
the personalised information delivery system.
• Other analysed variables such as gender, number of semesters of
enrolment with a virtual university and family responsibilities do not
determine differences in the personal information behaviour of e-
learning students.
51

52. 8. Conclusions
• Hypothesis 2: E-learning students can adopt different
personal information behaviour patterns in their academic,
workplace and daily life contexts, while the information-related
competencies acquired in any of the contexts are transferred to
the other contexts.
Research question:
f) Is it possible the transfer of information-related competencies
from/to academic, daily life and workplace contexts? (Paper IV)
52

53. 8. Conclusions
f) There is some transfer of information-related competencies between
workplace, daily life and academic contexts, but this is only at a basic
level of information literacy expertise:
• The cognitive approach (disciplined / chaotic) is not relevant for
behaving as expert or non-expert in information-related
competencies in all of the three contexts.
53

54. 8. Conclusions
• The relationship between information-related competencies’ expertise,
attitude and cognitive approach is different for each context:
– In the workplace, being expert in information literacy is
associated with having an implicated attitude and a
disciplined cognitive approach.
– In daily life, the information-related competencies do not
show any clear relationship with cognitive approach.
– In the academic context, the observed low level of
information literacy seems to be related with a prevalent
uninvolved attitude with chaotic features.
54

55. 8. Conclusions
• There is a regular pattern involving the cognitive approach and
attitude. If people are implicated, they will also develop a disciplined
cognitive approach, while if they are uninvolved, they behave
informationally chaotic.
55

56. PhD Defense
Towards a personalised virtual library:
indications from navigational and personal
information behaviour of e-learning students
Thank you for your attention.