Proposed framework for employing cognitive process for resolving programming problems for novice programmers

Ramírez, Carlos Enríquez; Herrero, Mariza Raluy; Sosa, Luz Maria Vega

doi:10.1109/conisoft50191.2020.00036

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…A series of papers about learning programming [58][59][60] discussed threshold concepts and the need to understand where students get "stuck. " Reference [16] speculates that "a feedback mechanism [could] be incorporated to ensure better results in the code deliveries and enhance the management of cognitive processes as an effective strategy for solving problems" (p. 196). Problets aligns well with this metacognitive approach through practice problems that provide feedback to students with step-by-step explanations.…”

Section: Difficulties In Introductory Programmingmentioning

confidence: 99%

Identifying Informatively Easy and Informatively Hard Concepts

Paul

BucciAnthony²,

KumarAmruth

et al. 2021

ACM Trans. Comput. Educ.

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In this article, we leverage ideas from the theory of coevolutionary computation to analyze interactions of students with problems. We introduce the idea of informatively easy or hard concepts. Our approach is different from more traditional analyses of problem difficulty such as item analysis in the sense that we consider Pareto dominance relationships within the multidimensional structure of student–problem performance data rather than average performance measures. This method allows us to uncover not just the problems on which students are struggling but also the variety of difficulties different students face. Our approach is to apply methods from the Dimension Extraction Coevolutionary Algorithm to analyze problem-solving logs of students generated when they use an online software tutoring suite for introductory computer programming called problets . The results of our analysis not only have implications for how to scale up and improve adaptive tutoring software but also have the promise of contributing to the identification of common misconceptions held by students and thus, eventually, to the construction of a concept inventory for introductory programming.

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Section: Difficulties In Introductory Programmingmentioning

confidence: 99%