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Streamlined OrchestrationStreamlined Technology-driven
Orchestration
Lighton Phiri
Supervisors:
A/Prof. Hussein Suleman
Prof. Dr. Christoph Meinel
April 11, 2016
Introduction (1)
2
Formal learning spaces are inherently complex
ecosystems—actors, activities, constraints.
Source: http://www.uct.ac.za
Introduction (2)
3
Formal learning spaces can be turned into effective learning
environments by supporting educators with orchestration.
Source: http://www.uct.ac.za
Orchestration is challenging& ad hoc
Orchestration is challenging due to its multi-facented
nature
● Constraints such as time
Orchestration is ad hoc—no standard way of orchestrating
learning activities
● Analysis 1: Expert review sessions
○ Eight UCT teaching staff
● Analysis 2: Classroom observations
○ END1020S; END1021F; STAT1100S
● Analysis 3: UCT archived lecture recordings
○ Comprehensive analysis of ad hoc orchestration
4
Thesis statement
Streamlined orchestration—attainable through explicit
organisation of enactment activities using an
orchestration workbench—could potentially make
educators more effective.
Research questions
1) Does an orchestration workbench enable educators to
become more effective?
2) What is the impact of an orchestration workbench on
educators’ teaching experience?
5
Study 1: Ad hoc vs. organised
orchestration
6
PortableApps—ad hoc orchestration
Workbench prototype interface—organised orchestration
PortableApps Prototype Workbench
Study objectives
How does effectiveness & UX of organised orchestration,
using an orchestration workbench, compare with ad hoc
orchestration?
● H1: Workbench is more effective
● H2: Workbench results in positive user experience
7
RQ AH Factor Variable Scale Description
RQ1 H1
Task speed Tt
Min Task time
Success PQ [-3 – 3] Pragmatic quality
Comfort HQ-I [-3 – 3] Hedonic identification
RQ2 H2 UX HQ-I;ATT [-3 – 3] Hedonic; attractiveness
Experimental variables & conditions
● Within group experiment involving 29 participants
○IV: orchestration technique
○DV: time on tasks; AttrakDiff 2 dimensions
○Control variables: ISP levels; Teaching experience; Computing
experience
8
Pre-task
activities
Orchestration
tasks
Post-task
activities
Experimental procedure (1)
● Study briefing and consent
● Demographic information
○ISP level
○Teaching experience
○Computing experience
9
Pre-task
activities
Orchestration
tasks
Post-task
activities
Experimental procedure (2)
● Random experimental blocks
10
Pre-task
activities
Orchestration
tasks
Post-task
activities
Participants Approach 1 Approach 2
Group 1 15 Workbench PortableApps
Group 2 14 PortableApps Workbench
Experimental procedure (3)
● Guided orchestration
○Directed sequencing of learning activities
● Learning scenario
○Lesson 1.1—Natural Sciences and Technology, Grade 5–B
○(1) Lesson -> (2) Video -> (3) Activity -> (4) Investigation
11
Pre-task
activities
Orchestration
tasks
Post-task
activities
Experimental procedure (4)
● AttrakDiff 2 ‘Comparison A–B’
○Approaches—PortableApps& Workbench UI
○(1) Approach #1 -> (2) Approach #2
● Debriefing
○Study summary
12
Pre-task
activities
Orchestration
tasks
Post-task
activities
Results 1: Time on tasks (1)
● On average, orchestration of learning activities was
14.7% faster using workbench
13
p > 0.05—no statistically significant difference
Results 2: AttrakDiff 2 (1)
AttrakDiff 2 portfolio-
presentation
● Both orchestration
approaches fall within the
same character region
● Workbench approach falls
closer to desired character
region
14
Results 2: AttrakDiff 2 (2)
AttrakDiff 2 dimension means
● PQ; HQ-I; ATT
○Mean score higher for
workbench
● HQ-S
○Mean score higher for
PortableApps
Further analysis of dimension
means done using word-pairs
15
p > 0.05—no statistically significant difference
Results 3: Counterbalancing&
demographics
● Counterbalancing
○Time on tasks
■Participants in Group 1 36.2% faster using workbench
■Participants in Group 2 5.2% faster using PortableApps
○AttrakDiff dimensions
■Similar trend observed for counterbalanced group, as with
overall results
● Demographic differences
○Some correlation between demographics—ISP level, teaching
experience and computing experience—and time taken to
orchestrate activities.
16
Study findings
Effectiveness
● Learning activities orchestrated faster using
workbench
● Perceived success more pronounced with workbench
User experience
● Higher mean score for HQ-I and ATT dimensions
Validity of results
● No statistical significance
○Only 29 of planned 52 participants took part in study
○Study to be replicated with additional participants
17
Study 2: Orchestrating a flipped class
18
CSC2002S—Computer Architecture course outline
structure.
Source: https://youtu.be/x5s0aENwNMA
Study 2: Orchestrating a flipped class
19
CSC2002S—Computer Architecture course outline
structure.
Source: https://youtu.be/x5s0aENwNMA
Study objectives (1)
Study aimed at assessing the feasible and potential of
organised orchestration in authentic educational settings.
● To what extent does workbench approach aid
orchestration?
● What is the potential impact of workbench approach
on learning?
20
RQ Object Variable Scale Description
RQ1
Educator Var Min App usage
Educator PQ [-3 – 3] Interviews
RQ2 Learners Questionnaire [-3 – 3] Subjective
Study objectives (2)
21
Workbench UI implemented to orchestrate core activities
Source: http://media.uct.ac.za
Evaluation procedure (1)
● Usage pattern analysis involved video analysis of
lecture recordings—”Presentation View”
○Opencast Matterhorn segmentation analysis
○11 sessions analysed
○Orchestration tools and usage frequencies noted
22
(1)
Usage
(2)
Educator
(3)
Learners
Evaluation procedure (2)
● Educator interaction with workbench tool was
evaluated two-fold
○Informal interview sessions
○Direct observations of tool use
23
(1)
Usage
(2)
Educator
(3)
Learners
Evaluation procedure (3)
● Learner survey conducted on last day of class to elicit
subjective experience
○71 participants recruited
○Static sequencing, learning activity organisation, and specific
prototype features
24
(1)
Usage
(2)
Educator
(3)
Learners
Analysis 1: Tool usage pattern
● Nine orchestration tools
used during duration of
course
○ Most tools used to render
content
○ Specialised tools once-off tasks
● On average prototype used
most of the time
○ Used 66.72% on average
○ Switching occurred an average
of two times with noticeable
time during switchover
25
Tool Freq. Duration
Workbench 10 00:30:31
VideoGlide 8 00:07:56
Firefox 1 00:21:29
Impress 1 00:38:26
Evince 1 00:00:50
QtSpim 1 00:12:47
Robotic Arm 1 00:01:24
TextEditor 1 00:02:07
VirtualBox 1 00:00:58
Analysis 2: Learner experience
● Tool helped organise activities
● Static sequencing (activity listing) found helpful
● Timer useful to average performers
26
Study findings
Feasibility of organised orchestration
● Facilitated neutral flow of activities
● Results from learner survey indicate tool was impact
neutral
Potential to facilitate improved learning outcomes
● Learner survey suggests orchestration workbench has
the potential to positively impact learning experience
27
Future directions
1) Replicate comparative study
○ Validity of results
2) Guided orchestration for peer learning
○ Authentic learning environment
○ Measuring orchestration load
3) Dynamic enactment of learning activities
○ Pre-session management
○ Measuring orchestration load
4) Comprehensive analysis of UCT lecture recordings
○ Support for Ad hoc orchestration claim
5) Sharable orchestration OERs
○ Reusable orchestration appliances
28
Bibliography
[1] Jeremy Roschelle et al. “Classroom Orchestration:
Synthesis”. Computers & Education, 6a9:523–526, 2013.
[2] Pierre Dillenbourg. “Design for Classroom Orchestration”.
Computers & Education, 69:485–492, 2013.
[3] Pierre Dillenbourg and Patrick Jermann. “Technology for
classroom orchestration”. New Science of Learning. 525–
552, 2011.
[4] Luis P. Prieto et al. “Orchestrating technology enhanced
learning: a literature review and a conceptual framework”.
International Journal of Technology Enhanced
Learning, 3(6):583, 2011.
29
Streamlined OrchestrationStreamlined Technology-driven
Orchestration
Lighton Phiri
Supervisors:
A/Prof. Hussein Suleman
Prof. Dr. Christoph Meinel
April 11, 2016

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Streamlined Technology-driven Orchestration

  • 1. Streamlined OrchestrationStreamlined Technology-driven Orchestration Lighton Phiri Supervisors: A/Prof. Hussein Suleman Prof. Dr. Christoph Meinel April 11, 2016
  • 2. Introduction (1) 2 Formal learning spaces are inherently complex ecosystems—actors, activities, constraints. Source: http://www.uct.ac.za
  • 3. Introduction (2) 3 Formal learning spaces can be turned into effective learning environments by supporting educators with orchestration. Source: http://www.uct.ac.za
  • 4. Orchestration is challenging& ad hoc Orchestration is challenging due to its multi-facented nature ● Constraints such as time Orchestration is ad hoc—no standard way of orchestrating learning activities ● Analysis 1: Expert review sessions ○ Eight UCT teaching staff ● Analysis 2: Classroom observations ○ END1020S; END1021F; STAT1100S ● Analysis 3: UCT archived lecture recordings ○ Comprehensive analysis of ad hoc orchestration 4
  • 5. Thesis statement Streamlined orchestration—attainable through explicit organisation of enactment activities using an orchestration workbench—could potentially make educators more effective. Research questions 1) Does an orchestration workbench enable educators to become more effective? 2) What is the impact of an orchestration workbench on educators’ teaching experience? 5
  • 6. Study 1: Ad hoc vs. organised orchestration 6 PortableApps—ad hoc orchestration Workbench prototype interface—organised orchestration PortableApps Prototype Workbench
  • 7. Study objectives How does effectiveness & UX of organised orchestration, using an orchestration workbench, compare with ad hoc orchestration? ● H1: Workbench is more effective ● H2: Workbench results in positive user experience 7 RQ AH Factor Variable Scale Description RQ1 H1 Task speed Tt Min Task time Success PQ [-3 – 3] Pragmatic quality Comfort HQ-I [-3 – 3] Hedonic identification RQ2 H2 UX HQ-I;ATT [-3 – 3] Hedonic; attractiveness
  • 8. Experimental variables & conditions ● Within group experiment involving 29 participants ○IV: orchestration technique ○DV: time on tasks; AttrakDiff 2 dimensions ○Control variables: ISP levels; Teaching experience; Computing experience 8 Pre-task activities Orchestration tasks Post-task activities
  • 9. Experimental procedure (1) ● Study briefing and consent ● Demographic information ○ISP level ○Teaching experience ○Computing experience 9 Pre-task activities Orchestration tasks Post-task activities
  • 10. Experimental procedure (2) ● Random experimental blocks 10 Pre-task activities Orchestration tasks Post-task activities Participants Approach 1 Approach 2 Group 1 15 Workbench PortableApps Group 2 14 PortableApps Workbench
  • 11. Experimental procedure (3) ● Guided orchestration ○Directed sequencing of learning activities ● Learning scenario ○Lesson 1.1—Natural Sciences and Technology, Grade 5–B ○(1) Lesson -> (2) Video -> (3) Activity -> (4) Investigation 11 Pre-task activities Orchestration tasks Post-task activities
  • 12. Experimental procedure (4) ● AttrakDiff 2 ‘Comparison A–B’ ○Approaches—PortableApps& Workbench UI ○(1) Approach #1 -> (2) Approach #2 ● Debriefing ○Study summary 12 Pre-task activities Orchestration tasks Post-task activities
  • 13. Results 1: Time on tasks (1) ● On average, orchestration of learning activities was 14.7% faster using workbench 13 p > 0.05—no statistically significant difference
  • 14. Results 2: AttrakDiff 2 (1) AttrakDiff 2 portfolio- presentation ● Both orchestration approaches fall within the same character region ● Workbench approach falls closer to desired character region 14
  • 15. Results 2: AttrakDiff 2 (2) AttrakDiff 2 dimension means ● PQ; HQ-I; ATT ○Mean score higher for workbench ● HQ-S ○Mean score higher for PortableApps Further analysis of dimension means done using word-pairs 15 p > 0.05—no statistically significant difference
  • 16. Results 3: Counterbalancing& demographics ● Counterbalancing ○Time on tasks ■Participants in Group 1 36.2% faster using workbench ■Participants in Group 2 5.2% faster using PortableApps ○AttrakDiff dimensions ■Similar trend observed for counterbalanced group, as with overall results ● Demographic differences ○Some correlation between demographics—ISP level, teaching experience and computing experience—and time taken to orchestrate activities. 16
  • 17. Study findings Effectiveness ● Learning activities orchestrated faster using workbench ● Perceived success more pronounced with workbench User experience ● Higher mean score for HQ-I and ATT dimensions Validity of results ● No statistical significance ○Only 29 of planned 52 participants took part in study ○Study to be replicated with additional participants 17
  • 18. Study 2: Orchestrating a flipped class 18 CSC2002S—Computer Architecture course outline structure. Source: https://youtu.be/x5s0aENwNMA
  • 19. Study 2: Orchestrating a flipped class 19 CSC2002S—Computer Architecture course outline structure. Source: https://youtu.be/x5s0aENwNMA
  • 20. Study objectives (1) Study aimed at assessing the feasible and potential of organised orchestration in authentic educational settings. ● To what extent does workbench approach aid orchestration? ● What is the potential impact of workbench approach on learning? 20 RQ Object Variable Scale Description RQ1 Educator Var Min App usage Educator PQ [-3 – 3] Interviews RQ2 Learners Questionnaire [-3 – 3] Subjective
  • 21. Study objectives (2) 21 Workbench UI implemented to orchestrate core activities Source: http://media.uct.ac.za
  • 22. Evaluation procedure (1) ● Usage pattern analysis involved video analysis of lecture recordings—”Presentation View” ○Opencast Matterhorn segmentation analysis ○11 sessions analysed ○Orchestration tools and usage frequencies noted 22 (1) Usage (2) Educator (3) Learners
  • 23. Evaluation procedure (2) ● Educator interaction with workbench tool was evaluated two-fold ○Informal interview sessions ○Direct observations of tool use 23 (1) Usage (2) Educator (3) Learners
  • 24. Evaluation procedure (3) ● Learner survey conducted on last day of class to elicit subjective experience ○71 participants recruited ○Static sequencing, learning activity organisation, and specific prototype features 24 (1) Usage (2) Educator (3) Learners
  • 25. Analysis 1: Tool usage pattern ● Nine orchestration tools used during duration of course ○ Most tools used to render content ○ Specialised tools once-off tasks ● On average prototype used most of the time ○ Used 66.72% on average ○ Switching occurred an average of two times with noticeable time during switchover 25 Tool Freq. Duration Workbench 10 00:30:31 VideoGlide 8 00:07:56 Firefox 1 00:21:29 Impress 1 00:38:26 Evince 1 00:00:50 QtSpim 1 00:12:47 Robotic Arm 1 00:01:24 TextEditor 1 00:02:07 VirtualBox 1 00:00:58
  • 26. Analysis 2: Learner experience ● Tool helped organise activities ● Static sequencing (activity listing) found helpful ● Timer useful to average performers 26
  • 27. Study findings Feasibility of organised orchestration ● Facilitated neutral flow of activities ● Results from learner survey indicate tool was impact neutral Potential to facilitate improved learning outcomes ● Learner survey suggests orchestration workbench has the potential to positively impact learning experience 27
  • 28. Future directions 1) Replicate comparative study ○ Validity of results 2) Guided orchestration for peer learning ○ Authentic learning environment ○ Measuring orchestration load 3) Dynamic enactment of learning activities ○ Pre-session management ○ Measuring orchestration load 4) Comprehensive analysis of UCT lecture recordings ○ Support for Ad hoc orchestration claim 5) Sharable orchestration OERs ○ Reusable orchestration appliances 28
  • 29. Bibliography [1] Jeremy Roschelle et al. “Classroom Orchestration: Synthesis”. Computers & Education, 6a9:523–526, 2013. [2] Pierre Dillenbourg. “Design for Classroom Orchestration”. Computers & Education, 69:485–492, 2013. [3] Pierre Dillenbourg and Patrick Jermann. “Technology for classroom orchestration”. New Science of Learning. 525– 552, 2011. [4] Luis P. Prieto et al. “Orchestrating technology enhanced learning: a literature review and a conceptual framework”. International Journal of Technology Enhanced Learning, 3(6):583, 2011. 29
  • 30. Streamlined OrchestrationStreamlined Technology-driven Orchestration Lighton Phiri Supervisors: A/Prof. Hussein Suleman Prof. Dr. Christoph Meinel April 11, 2016