Transcript
Remedial Online Teachingon a Summer Course
Martin Rehm
MGSoG Young Talent Day29th November, 2007
… and more
Outline
• Framework• Online Remedial Teaching Model• Research Questions• Methodology• Results• More Results• Outlook
Framework
• Increasing internationalization of enrollment(~ 70% from abroad)
• ‘New’accreditation procedures (Treaty ofBologna)
• Differences in prior knowledge• Incentive problems of physical summer course
Online Remedial Teaching Model
1. Online Availability 24/7(Vrasides & Zembylas, 2003)
2. Adaptive(Falmange et al., 2004)
3. Rapid feedback(Draaijer, 2004, Vrasides & Zembylas, 2003)
4. Interactive(Bryant et al. 2005, Ronteltap & Van der Veen, 2002)
5. Flexible Learning Methods & Assessment(Marshall, 2003, Segers, 2004)
Technology24/7 online
Student Student
Teacher
Feedback
Interaction Feed
back
Inte
ract
ion
Feedback
Interaction
FeedbackAdaptive Feed
back
Adapti
ve
Virtual Learning Environment
Research Questions
1. How can students assess their current level ofmastery before joining a (Bachelor’s) programme?
2. If the level of mastery of an individual studentseems too low, how can an online summer coursehelp to tackle this deficiency?
3. How can online summer courses be designed toincrease the completion rates of students who enrollto them?
Methodology
Prior Knowledge Test
• Diagnostic Test• Self-Assessment• Feedback via email
• ~ 70 % of incoming students are belowpredefined threshold level
Online Course Economics
• 6 weeks• 10 –15 hours per week• e-PBL approach• ~ 15 participants per group• Online Course Materials• EleUM (POLARIS)• Checkup Tests (formative)• End Assessment (summative)
• Peer Evaluation
Virtual Learning Environment
Technology24/7 online
Student Student
Teacher
Feedback
Interaction Feed
back
Inte
ract
ion
Feedback
Interaction
FeedbackAdaptive Feed
back
Adapti
ve
Results
• Pre-Evaluation:– dissatisfied with their level of mastery in economics– appreciated:
•online nature of the course•collaborative learning
• Passing Rate:– 1st Version: 50 %– OSCE 2007 (MGSoG): 92 %
• End Evaluation:– Café-Talk Forum– very good …
More Results (1)
50
55
60
65
70
75
80
85
90
95
100
EconPrior NoEconPrior SC-pass SC-fail
Figure 1: Passing rates EcBus (%)
More Results (2)
5,4
5,6
5,8
6
6,2
6,4
6,6
6,8
7
7,2
7,4
EconPrior NoEconPrior SC-pass SC-fail
Figure 2: Average grades final exam EcBus (0-10)
More Results (3)
• Selection Bias?– if any, it is very small & statistically insignificantè Suggests a true learning effect
• Impact of CSCL on the quality of the learning
process of novice students?– Based on Schellens & Valcke (2005)– Opposite results (different type of sample)
Outlook
1. Does CSCL have a temporary or structural effect onthe (prior) knowledge level and competencies ofstudents?
2. Research is needed on the motivation ofparticipants.
3. More specified and detailed information about thesubgroups.
Bachelor è Master è Professionals
Social Network Analysis
CSCL
Macro
MezzoHierarchy A
Hierarchy B
Social Network Analysis
CSCL
MicroType A
Type B
Social Network Analysis
CSCL
Remedial Online Teachingon a Summer Course
Martin Rehm
MGSoG Young Talent Day29th November, 2007
… and more
top related