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Using a digital tool to improve students’ algebraic expertise in the Netherlands:
crises, feedback and fading
Christian Bokhove
Southampton Education School
April 17th, 2014, BCME-8
Rationale
Algebraic skills Year 12 students Netherlandsoftendisappointing
But even when rewriting skills are OK…
…many things can go wrong
So conceptual understanding and pattern recognition are important!
Use of ICT
So can’t we use ICT for acquiring, practicing and assessing algebraic
expertise?
Research questions:What is the effect of an intervention on the development of algebraic expertise, including both procedural skills and symbol sense? Which factors predict the resulting algebraic performance?
Conceptual framework, elements of:
• Symbol sense – basic skills (e.g. Arcavi)
• Formative – summative assessment (e.g. Black & Wiliam)
• Feedback
Research set-up
Rnd Focus Target N
Pre What software, what characteristics?
Experts
1 Could it work? 1-to-1s, qualitative
N=5
2 In what way can it work?
2 classes in 1 school
N=31
3 Does it work? 9 schools, quantitative
N=324
Third round design
• 324 students in 9 schools (N=324)
• Year 12, nature and health stream
• Digital module: 6 hours, 6 parts
• Teachers were free in how to deploy the module, but were asked afterwards
• Data collection
– Scores pen-and-paper pre- and posttests
– Scores and logfiles
–Questionnaires
Equations: in-between steps, multiple strategies allowed
Store student results, and use these as a teacher to study misconceptions and for starting classroom discussions
students
(i) students learn a lot from what goes wrong,
(ii) but students will not always overcome these if no feedback is provided, and
(iii) that too much of a dependency on feedback needs to be avoided, as summative assessment typically does not provide feedback.
These three challenges are addressed by principles for crises, feedback and fading, respectively.
Crisis-tasks“students learn a lot from what goes wrong”
“Failure is, in a sense, the highway to success” - Keats
Feedback: overcoming a crisis
Screencast clips
“but students will not always overcome these if no feedback is provided”
Feedback: worked examples and hints
IDEAS feedback, webservice with Jeuring et al
Fading“too much of a dependency on feedback needs to be avoided”
Posttest (M=78.71, SE=15.175) is significantly higher than the pretest score (M=51.55, SE=21.094), t(285)=-22.589, p<.001, r=.801, d=-1.34.
Symbol sense score on the posttest (M=1.462, SE=1.504) is significantly higher than the pretest score (M=-1.493, SE=2.339), t(285)=-20.602, p<.001, r=.773, d=-1.22.
Effect
Significant predictors higher posttest score
• Previous knowledge
• Time spent in self-test and summative-test modes
• General attitude towards mathematics
Non-significant predictors higher posttest score
• Gender
• Attitude towards ICT
• Total time spent on module
• More time spent at home or at school
Predictors
New developments
