Evidence based practices in elearning collaborative learning in higher education empirical evidence
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Evidence-based practices in elearning. Collaborative learning in higher education: empirical evidence. Prof. dr. Martin Valcke http://allserv.ugent.be/~mvalcke/CV/CVMVA.htm Hamburg February 4, 2007 . Structure. Collaborative learning without ICT Setting the scene

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Evidence based practices in elearning collaborative learning in higher education empirical evidence

Evidence-based practices in elearning. Collaborative learning in higher education: empirical evidence.

Prof. dr. Martin Valcke

http://allserv.ugent.be/~mvalcke/CV/CVMVA.htm

Hamburg

February 4, 2007


Structure
Structure

  • Collaborative learning without ICT

  • Setting the scene

  • But does it lead to learning?

  • Group characteristics

  • Task characteristics

    • Scripting

    • Roles

    • Tagging

  • Student characteristics & support: peer tutoring

  • Conclusions


Conclusions
Conclusions

  • Collaborative learning: don’t forget « lessons learned »

  • Collaborative learning is part of larger learning environment

  • Adding structure is the key: roles, scripting, tagging

  • Coaching, tutoring, … has an impact

  • Management issues


« Collaborative learning is in the air »

« Everyone wants it. It is the instructional strategy, perhaps the strategy of the decade »



Collaborative learning without ict
Collaborative learning without ICT?

  • Meta-analysis collaborative learning research

    • Slavin (1996)

    • Johnson & Johnson (1989)

  • “The research has an external validity and a generalizability rarely found in the social sciences.”


Collaborative learning without ict1
Collaborative learning without ICT?

  • Consistent and overwhelming positive impact on performance, motivation, social skills, development of metacognition, etc.

  • But, why has it not been implemented to a larger extent?


Design guidelines
Design guidelines

  • Garantee that there are shared learning objectives in a team

  • Build on team responsibility to reach the goals.

  • Build individual responsibility to reach goals.

  • Guarantee equal opportunities in the team activities.

  • Embed a level of competition and/or comparision.


Design guidelines1
Design guidelines

  • Break down larger tasks into subtasks.

  • Take into account individual differences (level, interest, intentions, ...).

  • Blend group activities with face-to-face activities.

  • Develop communication skills.

  • Monitor communication processes.


Setting the scene
Setting the scene

  • University

  • Large groups of 1st year students (N=286)

  • Online learning environment

  • Computer Supported Collaborative Learning (CSCL): part of this environment

  • Course ‘Instructional Sciences’

  • 35 groups of 8 students working in online groups



But does this invoke relevant learning
But does this invoke relevant learning?

  • Collaboration does not lead automatically to high quality learning.

  • There is a need guidance and online support in CSCL settings that is comparable to the need of classroom support in face-to-face settings (Lazonder, Wilhelm, & Ootes, 2003).


But does this invoke relevant learning1
But does this invoke relevant learning?

  • First generation CSCL-research:

    • Naive use of cooperative learning

    • Medium orientation

    • Neglection of context / individual / objectives

    • Over-estimation of potential technology


Does it invoke relevant learning
Does it invoke relevant learning?

  • First generation:

    • Management problems

    • No insight into structure of dicsussion

    • Low task focus (Henri, 1982)

    • Low levels of cognitive processing: new facts, concepts; hardly theory construction, application, evaluation

    • Time on task problem

    • What with students who are not active?


But does this invoke relevant learning2
But does this invoke relevant learning?

  • Second generation CSCL-research:

    • Focus on “affordances”

    • Attention paid to “design guidelines”


Applying design guidelines
Applying design guidelines

  • Shared learning objectives

  • Team responsibility

  • Individual responsibility

  • Equal opportunities

  • Level of competition or comparision.


Applying design guidelines1
Applying design guidelines

  • Subtasks.

  • Individual differences

  • Blend group and face-to-face activities

  • Develop communication skills.

  • Monitor communication processes


Design guidelines 3 sets of variables
Design guidelines ~ 3 sets of variables

Learner characteristics

& support

Task

characteristics

Group

Characteristics


Design guidelines 3 sets of variables1
Design guidelines ~ 3 sets of variables

  • Group:

    • Size

    • level of interaction

  • Task characteristics:

    • Nature of task (open, theme)

    • Roles (content)

    • Roles (communication)

    • Tagging

    • Timing of role assignment

  • Learner: characteristics and support


Learning nature of dependendent variables
Learning:Nature of dependendent variables

  • Level of interaction

  • Level of knowledge construction

  • Learning performance (test scores)

  • Level of critical thinking

  • Self & group efficacy



Group size

Differential impact

Group size

small (8-10), average (11-13 , large (15-18)




Roles
Roles

  • Pharmacy education

  • 5th year students

  • 5 months internship

  • Lack of integrated pharmaceutical knowledge


Roles1
Roles

  • Content roles:

    • Pharmacyst

    • Pharmacyst assistant

    • Theorist

    • Researcher

    • Intern

  • Communication roles:

    • Moderator

    • Question-asker

    • Summarizer

    • Source researcher



ICS

Integrated Curriculum Score

S. TIMMERS, M. VALCKE*, K. DE MIL & W.R.G. BAEYENS (in press).

The Impact of Computer Supported Collaborative Learning on Internship

Outcomes of Pharmacy Students. Interactive Learning Environments


LKC

Level knowledge Construction

S. TIMMERS, M. VALCKE*, K. DE MIL & W.R.G. BAEYENS (in press).

The Impact of Computer Supported Collaborative Learning on Internship

Outcomes of Pharmacy Students. Interactive Learning Environments


Timing roles
Timing roles

  • 1ste year course “instructional sciences”

  • N 250

  • 20 discussion groups

  • Transcripts of the entire 12 week discussion period

  • 4 discussion themes of 3 weeks each

  • About 4818 messages or 60450 lines of text




Roles2
Roles

  • Starter: start off the discussion, give new impulses every time the discussions slack off

  • Moderator: monitor the discussions, stimulate other students, ask critical questions, inquire for opinions

  • Theoretician: bring in theory, ensure all relevant theoretical concepts are used in the discusion

  • Sourcesearcher: seek external information on the topics, go beyond the scope of course reader

  • Summarizer: post interim summaries, make provisional conclusions, post final summary




Gunawardena lowe anderson 1997
Gunawardena, Lowe, & Anderson (1997)

  • Level 1: sharing/comparing of information

  • Level 2: the discovery and exploration of dissonance or inconsistency among ideas, concepts or statements

  • Level 3: negotiation of meaning / co-construction of knowledge

  • Level 4: testing and modification of proposed synthesis or co-construction

  • Level 5: agreement statement(s) / applications of newly constructed meaning



Timing introduction roles3
Timing: introduction roles

  • Role/No-Role condition reaches significantly higher levels of knowledge construction in two themes

  • Even when the role support is cut back




“There is a differential impact of the different roles”

Differential impact roles

Source Searcher

=

Theoretician

+

Summarizer

+++

Moderator

+

=

Starter

No role

+

Ref.cat.

No role condition




Tagging2
Tagging

  • Aims of tagging:

    • it obliges students to reflect upon the nature of their contribution and on how it will add to the ongoing discussion

    • the labels improve the outline of the discussion and indicate the predominance or absence of one or more thinking types

  • Example: De Bono’s (1991) thinking hatsin view of developing critical thinking


Tagging3
Tagging

  • Garrison (1992) identifies five stages of critical thinking:

  • Problem identification

  • Problem definition

  • Problem exploration

  • Problem evaluation/applicability

  • Problem integration



Tagging4
Tagging

  • 3th-year university students

  • enrolled for the course ‘Instructional Strategies’ (N=35)

  • 6 groups of 6 team members

Tag posts by a thinking hat

No tags to posts required


Tagging5
Tagging

  • Evidence for critical thinking in both conditions

  • Significant deeper critical thinking in experimental condition (F(1, 416)=364.544; p<.001)


Tagging6
Tagging

  • Patterns are quite similar for both conditions

  • Experimental condition

    • more focused discussions (F(1, 415)=1550.510; p<.001)

    • more new info and ideas (F(1, 352)=21.955; p<.001)

    • more linking facts ideas (F(1, 31)=3.024; p<.092)


Impact of tagging
Impact of tagging

  • Multinomial logistic regressions indicate that

  • being in the experimental condition increases the probability of engaging in in-depth discussions radically(p<.001)

  • experimental students post 2.73 as many messages adding new problem-related information to the discussion (p=.001)

  • experimental students were 2.95 times more likely to add new ideas for discussion (p=.009).

  • linking ideas and critical assessment occur rarely. When it occurs, it is in the experimental condition.


Impact of tagging over time
Impact of tagging over time

  • Experimental students show a rather constant level of critical thinking

  • Control students show a decrease during problem identification (F(1, 416)=1408.838; p<.001) and exploration(F(1, 415)=1101.513; p<.001)


But ….

  • Studies with freshman: no significant impact.

  • Tagging interferes with knowledge construction process.

  • BUT … tutoring helps


But …

  • More critical thinking in labeling condition after correction for the different tutor styles

    • Overall depth of CT

    • Importance

    • Discussion of ambiguities

    • Input of new information

    • Linking of information

    • Critical assessment

    • Defining the problem

    • Integrating new knowledge



Support peer tutors
Support: peer tutors

  • Given critical results of some CSCL-studies, demand for structure:

    • Scripting (roles, tagging, …)

    • Facilitators (Bonk, Wisher, & Lee, 2004; Garrison, Anderson, & Archer, 2000; Rickard, 2004; Salmon, 2000)

    • Prior research, however, revealed that peer tutors were mainly engaged in social support, while less attention was paid to stimulating ‘knowledge construction’ and ‘personal development’(De Smet, Van Keer, & Valcke, in press)

    • Therefore extra support for tutors


Method
Method

  • Effect study: Impact of labeling on patterns in tutor support.

  • E-moderating model(Salmon, 2000)


Peer tutoring
Peer tutoring

  • Cross-age peer tutoring blended in with online discussion groups

  • One peer clearly takes a supportive role

  • Fourth-year students help freshmen

  • Ratio = 1/10

  • Open-ended group assignments

  • 2 weeks discussion per theme

  • 1 trial discussion and 4 discussion themes


3 tutor training conditions
3 tutor training conditions

  • Control (N=39)

  • All-round instructions, No labeling requirements,

  • No pre-service exercises, Focus groups

  • Labeling (N=18)

  • E-moderating instructions, Labelling requirements

  • Pre-service exercises, Focus groups

  • Non-labeling (N=17)

  • E-moderating instructions, No labeling requirements,

  • Pre-service exercises, Focus groups


Labeling tutoring activity
Labeling tutoring activity

  • Labeling involves self-monitoring

  • E-moderating taxonomy (Salmon, 2000)

  • Access and motivation (Step 1)

  • Socialisation (Step 2)

  • Information-exchange (Step 3)

  • Knowledge construction (Step 4)

  • Personal development (Step 5)



Impact of labeling in tutoring
Impact of labeling in tutoring

  • Multinomial logistic regression analysis >>

  • Variables treated as nominal

  • Independent of the training condition, tutors filled all the roles required of e-moderators

  • In each training condition, vast majority for ‘information-exchange’ (step 3)


Impact of labeling in tutoring1
Impact of labeling in tutoring

  • Compared to the control condition, both the labelling and non-labeling condition positively influenced the adoption of tutoring support that stimulates:

    • ‘socialisation’ (step 2)

    • ‘information-exchange’ (step 3)

    • ‘personal development’ (step 5)

  • Labelling enhanced tutors’ facilitation for ‘personal development’ (step 5)


Conclusions1
Conclusions

  • Collaborative learning: don’t forget « lessons learned »

  • Collaborative learning is part of larger learning environment

  • Adding structure is the key: roles, scripting, tagging

  • Coaching, tutoring, … has an impact

  • Management issues


Publications
Publications

  • De Smet, M., Van Keer, H., & Valcke, M. (in press). Blending asynchronous discussion groups and peer tutoring in higher education: An exploratory study of online peer tutoring behaviour. Accepted for publication in Computers and Education.

  • De Smet, M., Van Keer, H., & Valcke, M. (in press). Cross-age peer tutors in asynchronous discussion groups: A study of the evolution in tutor support. Accepted for publication in Instructional Science.

  • De Wever, B., Schellens, T.,Valcke, M & Van Keer, H. (2006). Content analysis schemes to analyze transcripts of online asynchronous discussion groups: a review. Computers & Education, 46(1), 6-28.

  • De Wever, B., Van Keer, H., Schellens, T., & Valcke, M. (in press). Applying multilevel modelling on content analysis data: Methodological issues in the study of the impact of role assignment in asynchronous discussion groups. Accepted for publication in Learning and Instruction.

  • De Wever, B., Van Winckel, M. & Valcke, M. (in press). Discussing patient management online: The impact of roles on knowledge construction for students interning at the paediatric ward. Accepted for publication in Advances in Health Sciences Education.

  • Schellens, T. & Valcke, M. (2005). Collaborative learning in asynchronous discussion groups: What about the impact on cognitive processing? Computers in Human Behavior, 21(6), 957-975.


Publications1
Publications

  • Schellens, T. & Valcke, M. (2006). Fostering knowledge construction in university students through asynchronous discussion groups. Computers & Education. 46(4), 349-370.

  • Schellens, T., Van Keer, H. & Valcke, M. (2005). The impact of role assignment on knowledge construction in asynchronous discussion groups: a multilevel analysis. Small Group Research, 36, 704-745.

  • Schellens, T., Van Keer, H., & Valcke, M. (2007). Learning in asynchronous discussion groups: A multilevel approach to study the influence of student, group and task characteristics. Accepted for publication in Journal of Behavior and Information Technology. 26(1), 55-71.

  • Schellens, T., Van Keer, H., De Wever, B., Valcke, M. (in press). Tagging Thinking Types in Asynchronous Discussion Groups: Effects on Critical Thinking. Accepted for publication in International Journal of Interactive Learning Environments.

  • Timmers, S., Valcke, M., De Mil, K. & Baeyens, W.R.G. (in press). CSCLE and internships of pharmacy students - The Impact of Computer Supported Collaborative Learning on Internship Outcomes of Pharmacy Students. Accepted for publication in International Journal of Interactive Learning Environments.

  • Valcke, M. & De Wever, B. (2006). Information and communication technologies in higher education: Evidence-based practices in medical education. Medical Teacher, 28, 40-48.


Evidence based practices in elearning collaborative learning in higher education empirical evidence1

Evidence-based practices in elearning. Collaborative learning in higher education: empirical evidence.

Prof. dr. Martin Valcke

http://allserv.ugent.be/~mvalcke/CV/CVMVA.htm

Hamburg

February 4, 2007