Integrating Rule-Based and Input-Based Approaches for Better Error Diagnosis in Expression Manipulation Tasks

Prank, Rein; Issakova, Marina

doi:10.1142/9789812776006_0010

Cited by 8 publications

(3 citation statements)

References 11 publications

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“…T-algebra is an interactive exercise environment for Basic School Algebra (Prank et al, 2007). A system of task types and difficulty levels and the functioning of random generation at each level can be observed when trying to compose task files with the T-algebra teacher program (T-algebra).…”

Section: Related Workmentioning

confidence: 99%

“…Many task types in our package for Mathematical Logic (Prank, 1991) and all the 60+ task types in Talgebra (Prank et al, 2007) contain random generation of exercises. We have had many discussions with university colleagues and school teachers about their expectations in that regard.…”

Section: Desired Features Of a Generation Algorithm And Teacher Controlmentioning

confidence: 99%

“…In 1987-1993 we computerized ten 90-minute exercise labs together with homework and tests. The computerized exercise labs were introduced in our third-semester course Introduction to Mathematical Logic, beginning from 1991 (Prank, 1991).…”

Section: Our Software For Propositional Logicmentioning

confidence: 99%

See 2 more Smart Citations

What Should We Add to Syntax-oriented Generation of Random Expressions to Meet Pedagogical Needs?

Prank

2016

Proceedings of the 8th International Conference on Computer Supported Education

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The paper looks for an exercise environment where the teacher program would enable to fix parameters of random generation so that the generated tasks have desired pedagogical properties. In particular, it should be possible to prescribe qualitative content and size of the solution and its parts, opportunities to make certain errors, probabilities of different decisions to be made by the student. We analyse two existing environments for algebraic exercises in Propositional Logic and identify what additional options are necessary and what computational engines or precomputed resources could produce the desired properties.

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Section: Related Workmentioning

confidence: 99%

Section: Desired Features Of a Generation Algorithm And Teacher Controlmentioning

confidence: 99%