Multilevel analysis of collaborative activities based on a Mobile Learning Scenario for real...
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Multilevel analysis of collaborative activities
based on
a Mobile Learning Scenario
for real classrooms
Irene-Angelica Chounta, Adam Giemza, H. Ulrich Hoppe
Collide, University of Duisburg-Essen
{chounta, giemza, hoppe}@collide.info
Mobile learning: a special case of learning....
� Learning on the move, across space, within context
� Activities supported by mobile devices
− „location-based“ scenarios with spatially distributed learning stations (museum, outdoor trips etc)
− smartphones, tablets etc.
� The activity analysis is carried out with qualitative methods
Objectives of the study
� Introduction of a mobile learning scenario in traditional school classrooms
� Use of common learning analytics within a mobile learning context
� Study of collaborative learning activities on multiple levels of analysis
a mobile learning scenario for the classroom
� Computer Kit: „Learn how to assemble a Personal Computer with Mobilogue“
a mobile learning scenario for the classroom
� QR codes as learning station/ computer parts markers in a very localized setting
Learning Content Video Quiz Scores
Mobilogue Architecture
� Authoring environment for the creation of new activities
� Activity logs for recording and post analysis
� Online Management Environment
Method of the study
� Two case studies:
− Case A: preliminary study, 17 students
− Case B: main study, 24 students
� Task: Group of students working together to assemble a pc
� Each group was supported by one mobile device
� The activities were analyzed with respect to:
- students practice on the individual and the group level
- group characteristics
- learning outcome
13 – 15 years old
Method of the study
� For the analysis we used:
- Activity metrics from logfiles - Average time gap among consequent actions
- Average response time to quizzes
- Quiz score
- Experts observations
- Activity transcripts (recorded by students)
- Users questionnaires (with respect to user experience and motivation for collaboration)
- Pre and Post Knowledge Tests (each test consisted of a ten-items questionnaire)
Case study A - Results
� 17 students randomly grouped in 5 groups
� Activity duration ≈ 90 minutes
� Group profiles based on pre-tests:
� One „strong“ team (team A)
� One „weak“ team (team E)
� Three average teams (teams B, C, D)
Pretest Scoresavg_group max_idv
teamA 6.25 8teamB 3.75 5teamC 4.33 5teamD 2.67 4
teamE 1 1
heterogeneous
homogeneous
Case study A - Results
� Greatest improvement � teams of average performance (on group and individual level)
� The “strong” team maintained the same score on average but scored less on the individual level - homogeneity increased)
� The “weak” team slightly improved – heterogeneity increased
� Heterogeneous teams increase homogeneity and vice versaPre-test Scores
avg_group max_idv
teamA 6.25 8teamB 3.75 5teamC 4.33 5teamD 2.67 4
teamE 1 1
Post-test Scoresavg_group max_idv
6.25 7
6.25 8
5.67 7
6.00 7
2.00 3
Pre-test Scoresavg_group max_idv
teamA 6.25 8teamB 3.75 5teamC 4.33 5teamD 2.67 4
teamE 1 1
Case study A - Results
� Quiz score reflects the knowledge test performance
� The average time gap correlates negatively with quiz score
� Teams with good knowledge background and high heterogenity move faster
Activity metrics
avg_timegapavg
response time
Quiz score
27.63 32.02 120
36.56 56.96 12037.14 23.70 100
37.91 31.55 90
38.43 57.43 80
Case study B - Results
� 24 students – 6 groups of four
� Groups were created by the teacher
� Activity duration ≈ 90 minutes
Special Additions / Modifications:
� Experts monitored the activity
� Students kept transcripts of group activity
� Students filled in questionnaires regarding their experience on collaboration
Case study B - Results
� Group profiles based on pre-tests:
� One strong team (team 03)
� Two weak teams (team 00 and team 05)
� Three average teams (teams 01, 02, 04)
� The Homogeneity of teams according to pre-test confirmed teacher‘s perception
Pre-test Scoresavg_group max_idv
team 00 2 4team 01 5.75 9team 02 4.25 5team 03 6.5 8team 04 5.5 7
team 05 1 2
heterogeneous
homogeneous
Case study B - Results� Group performance improved on average (47%) and
individual (31%)
� Max knowledge gain � weak team (team 05)
� Min knowledge gain � strong team (team 03)
� Knowledge „loss“ for the „strong“ students
� Homogenity increases for heterogenous groups and vice versa (confirming case study A)
Pre-test Scoresavg_group max_idv
team 00 2 4team 01 5.75 9team 02 4.25 5team 03 6.5 8team 04 5.5 7team 05 1 2
Post-test Scoresavg_group max_idv
3.5 77.5 86 7
6.5 77.25 8
6 9
Case study B - Results
� Heterogeneous teams achieved higher Quiz scores
� The average time gap correlates negatively with quiz score (also observed case study A)
� Heterogeneous teams move faster, i.e. Individuals take the lead
Activity metrics
avg_timegapavg
response time
Quiz score
20.89 51.88 120
23.42 49.02 12024.00 45.73 11025.84 61.99 9040.44 72.51 70
27.75 82.56 70
Pre-test Scoresavg_group max_idv
team 00 2 4team 01 5.75 9team 02 4.25 5team 03 6.5 8team 04 5.5 7team 05 1 2
Case study B - Results
� The students undertook three roles throughout the scenario:
� the operator of the mobile device
� the scriber and
� the assembler
0
0.2
0.4
0.6
0.8
1
1.2
1.4
u00-00 u00-01 u00-02 u00-03
team00
Scriber
Assembler
Operator
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0.2
0.4
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0.8
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u01-00 u01-01 u01-02 u01-03
team01
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1.4
u02-00 u02-01 u02-02 u02-03
team02
0
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0.8
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1.2
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u03-00 u03-01 u03-02 u03-03
team03
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u04-00 u04-01 u04-02 u04-03
team04
Scriber
Assembler
Operator
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u05-00 u05-01 u05-02 u05-03
team05
Scriber
Assembler
Operator
• 4 out of 6 teams followed no strict
role distribution
• Teams following strict role
distribution showed the lowest
knowledge & dissatisfaction
Discussion
� A mobile scenario to support collaborative activities for traditional classrooms
� Multilevel analysis of the activity (various methods and multiple units of analysis) to enhance the overall outcome
Learning Outcome
• The setting was more effective for students of weak and medium knowledge background
• Strong students/ teams showed little or no knowledge gain
• The students performance was increased on both individual and group level
Discussion
Group Characteristics & Learning Analytics
• Heterogeneous teams achieved higher game scores
• Game score did not correlate to knowledge gain or knowledge background
• Heterogeneous teams moved faster through the stages of the scenario
• Homogeneous teams tend to increase their heterogeneity and vice versa
Discussion
Collaboration
• Team members undertook roles with no particular plan
• In the case a strict plan was follows, it lead to frustration and low knowledge gain
• Strong students stated they would have done better on their own
• Weak/average students considered the activity as helpful
Conclusion and Future Work
� Multilevel analysis can provide valuable information and enhance mobile learning
� Extend the field of study to further investigate:
� the use of various scenarios
� varying degrees of freedom to classroom activities
� concurrent use of multiple devices within a team
� the nature of learning activities that could be supported effectively by the use of mobile devices
� ways to incorporate seamlessly mobile devices in traditional learning activities